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Journal articles
View DOI resources1
Abbatangelo M., Núñez Carmona E., Sberveglieri V., Comini E., and Sberveglieri G. (2020) “k-NN and k-NN-ANN Combined Classifier to Assess MOX Gas Sensors Performances Affected by Drift Caused by Early Life Aging”, Chemosensors, published by Svizzera.
View DOI resources2
Abbatangelo M., Núñez Carmona E., Sberveglieri V., Zappa D., Comini E., and Sberveglieri G. (2020) “An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs' Compliance with CFPR Guidelines”, Biosensors (Basel), published by MDPI, Basel.
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Amura A., Tonazzini A., Salerno E., Pagnotta S., and Palleschi V. (2020) “Color segmentation and neural networks for automatic graphic relief of the state of conservation of artworks”, Cultura e scienza del colore, published by Gruppo del Colore-Associazione Italiana Colore, Italia, Italia, vol. 12, pp. 7-15.
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Brook A., De Micco V., Battipaglia G., Erbaggio A., Ludeno G., Catapano I., and Bonfante A. (2020) “A smart multiple spatial and temporal resolution system to support precision agriculture from satellite images: Proof of concept on Aglianico vineyard”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 240.
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Capece N., Banterle F., Cignoni P., Ganovelli F., Erra U., and Potel M. (2020) “Turning a Smartphone Selfie into a Studio Portrait”, IEEE computer graphics and applications, published by National Computer Graphics Association, [Los Alamitos, CA], Stati Uniti d'America, vol. 40, pp. 140-147.
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Cupaioli F. A., Zucca F. A., Caporale C., Lesch K. P., Passamonti L., and Zecca L. (2020) “The neurobiology of human aggressive behavior: neuroimaging, genetic, and neurochemical aspects”, Progress in neuro-psychopharmacology & biological psychiatry, published by Pergamon, New York, Regno Unito.
View DOI resources7
Falavigna G. (2020) “Prediction of general medical admission length of stay with natural language processing and deep learning: a pilot study”, Internal and emergency medicine (Online), published by Springer Verlag Italia, Milano, Italia.
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Giordani T., Suprano A., Polino E., Acanfora F., Innocenti L., Ferraro A., Paternostro M., Spagnolo N., and Sciarrino F. (2020) “Machine Learning-Based Classification of Vector Vortex Beams”, Physical review letters, published by American Physical Society, College Park, MD, Stati Uniti d'America, vol. 124.
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Hu X., Shia L., Lin L., and Magliulo V. (2020) “Improving surface roughness lengths estimation using machine learning algorithms”, Agricultural and forest meteorology (Print), published by Elsevier, New York;, Paesi Bassi.
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La Tona G., Luna M., Di Piazza M. C., Pucci M., and Accetta A. (2020) “Development of a High-Performance, FPGA-Based Virtual Anemometer for Model-Based MPPT of Wind Generators”, Electronics (Basel), published by MDPI, Basel, vol. 9, 83 pages.
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Mantica P., Angioni C., Bonanomi N., Citrin J., Grierson B. A., Koechl F., Mariani A., and Staebler G. M. (2020) “Progress and challenges in understanding core transport in tokamaks in support to ITER operations”, Plasma physics and controlled fusion (Print), published by Institute of Physics, Bristol, Regno Unito, vol. 62.
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Marzi C. (2020) “Modeling Word Learning and Processing with Recurrent Neural Networks”, Information (Basel), ISSN 2078-2489, published by Molecular Diversity Preservation International-Basel, vol. 11(6), 14 pages.
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Marzi C. (2020) “Modelling the interaction of regularity and morphological structure: the case of Russian verb inflection”, Lingue e linguaggio, ISSN 1720-9331, published by Il Mulino, Bologna (Italia), vol. XIX(1), pp. 131-156.
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Massoli F. V., Amato G., and Falchi F. (2020) “Cross-resolution learning for face recognition”, Image and vision computing, published by Elsevier, Amsterdam, Paesi Bassi, vol. 99.
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May P. L., Leite D. S. C., Esuli A., Renso C., and Bogorny V. (2020) “MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings”, International journal of geographical information science (Print), published by Taylor & Francis, London, Regno Unito, vol. 34, pp. 1428-1450.
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Pati P., Jaume G., Fernandes L. A., Foncubierta A., Feroce F., Anniciello A. M., Scognamiglio G., Brancati N., Riccio D., Di Bonito M., De Pietro G., Botti G., Goksel O., Thiran J. P., Frucci M., and Gabrani M. (2020) “HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification”, ArXiv e-prints, published by Cornell University, Ithaca, NY, USA, Stati Uniti d'America.
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Pierangeli D., Marcucci G., Brunner D., and Conti C. (2020) “Noise-enhanced spatial-photonic Ising machine”, Nanophotonics (Berlin. Internet), published by De Gruyter, Berlin, Germania.
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Pourghasemi H. R., Gayen A., Lasaponara R., and Tiefenbacher J. P. (2020) “Application of learning vector quantization and different machine learning techniques to assessing forest fire influence factors and spatial modelling”, Environmental research (N. Y. N. Y., Print), published by Elsevier., Amsterdam, Stati Uniti d'America, vol. 184, pp. Art. 109321-1-Art. 109321-12.
View web resourcesView DOI resources19
Rossi R., Murari A., and Gaudio P. (2020) “On the Potential of Time Delay Neural Networks to Detect Indirect Coupling between Time Series”, Entropy (Basel, Online), published by MDPI, Basel, vol. 22, pp. 584-1-584-12.
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Roveda L., Maskani J., Franceschi P., Abdi A., Braghin F., Molinari Tosatti L., and Pedrocchi N. (2020) “Model-Based Reinforcement Learning Variable Impedance Control for Human-Robot Collaboration”, Journal of intelligent & robotic systems, published by Kluwer Academic Publishers, London;, Paesi Bassi.
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Savazzi S., Nicoli M., and Rampa V. (2020) “Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks”, IEEE Internet of Things Journal, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 7, pp. 4641-4654.
View web resourcesView DOI resources22
Seccia R., Gammelli D., Dominici F., Romano S., Landi A. C., Salvetti M., Tacchella A., Zaccaria A., Crisanti A., Grassi F., and Palagi L. (2020) “Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 15.
View web resourcesView DOI resources23
Segneri M., Bi H., Olmi S., and Torcini A. (2020) “Theta-Nested Gamma Oscillations in Next Generation Neural Mass Models”, Frontiers in computational neuroscience, published by Frontiers Research Foundation, Lausanne, Svizzera, vol. 14.
View web resourcesView DOI resources24
Shayeghi A., Azizian A., and Brocca L. (2020) “Reliability of reanalysis and remotely sensed precipitation products for hydrological simulation over the Sefidrood River Basin, Iran”, Hydrological sciences journal, published by published for the International Association of Hydrological Sciences by Blackwell, Oxford, Regno Unito.
View DOI resources25
Abbatangelo M., Núñez Carmona E., and Sberveglieri V. (2019) “Novel equipment for food quality control: An IoT nanowire gas sensors array”, Chemical Engineering Transactions, vol. 75, pp. 25-30.
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Amato G., Carrara F., Falchi F., Gennaro C., and Vadicamo L. (2019) “Large-scale instance-level image retrieval”, Information processing & management, published by Pergamon, New York, Regno Unito.
View web resourcesView DOI resources27
Anichini F., Banterle F., Buxeda I. G. J., Calleri M., Dershowitz N., Diaz D. L., Evans T., Gattiglia G., Gualandi M. L., Hervas M. A., Itkin B., Madrid I. F. M., Miguel G. E., Remmy M., Richards J., Scopigno R., Vila L., Wolf L., Wright H., and Zallocco M. (2019) “Developing the ArchAIDE application: A digital workflow for identifying, organising and sharing archaeological pottery using automated image recognition”, Internet archaeology, published by Department of Archaeology, University of York., York, Regno Unito, vol. 52.
View DOI resources28
Aronica S., Fontana I., Giacalone G., Lo Bosco G., Rizzo R., Mazzola S., Basilone G., Ferreri R., Genovese S., Barra M., and Bonanno A. (2019) “Identifying small pelagic Mediterranean fish schools from acoustic and environmental data using optimized artificial neural networks”, Ecological informatics (Print), published by Elsevier, Amsterdam, Paesi Bassi, vol. 50, pp. 149-161.
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Artusi A., Banterle F., Moreo A., and Carrara F. (2019) “Efficient Evaluation of Image Quality via Deep-Learning Approximation of Perceptual Metrics”, IEEE transactions on image processing (Online), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 29, pp. 1843-1855.
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Baeumer C., Heisig T., Arndt B., Skaja K., Borgatti F., Offi F., Motti F., Panaccione G., Waser R., Menzel S., and Dittmann R. (2019) “Spectroscopic elucidation of ionic motion processes in tunnel oxide-based memristive devices”, Faraday discussions (Print), published by Royal Society of Chemistry, Cambridge, England, Regno Unito, vol. 213, pp. 215-230.
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Bergomi M. G., Frosini P., Giorgi D., and Quercioli N. (2019) “Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning”, Nature Machine Intelligence, published by Springer Nature, vol. 1, pp. 423-433.
View web resourcesView DOI resources32
Brancati N., De Pietro G., Frucci M., and Riccio D. (2019) “A Deep Learning approach for breast invasive ductal carcinoma detection and lymphoma multi-classification in histological images”, IEEE access, published by Institute of Electrical and Electronics Engineers, Piscataway, NJ, Stati Uniti d'America, vol. 7, pp. 44709-44720.
View DOI resources33
Brusaferri A., Matteucci M., Portolani P., and Vitali A. (2019) “Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices”, Applied energy, published by Applied Science Publishers; [poi] Elsevier, London; [poi] Amsterdam, Regno Unito, vol. 250, pp. 1158-1175.
View web resourcesView DOI resources34
Capece N., Banterle F., Cignoni P., Ganovelli F., Scopigno R., and Erra U. (2019) “DeepFlash: turning a flash selfie into a studio portrait”, Signal processing. Image communication, published by Elsevier, Oxford;, Paesi Bassi, vol. 77, pp. 28-39.
View web resourcesView DOI resources35
Carrara F., Elias P., Sedmidubsky J., and Zezula P. (2019) “LSTM-based real-time action detection and prediction in human motion streams”, Multimedia tools and applications, published by Kluwer Academic Publishers, Dordrecht;, Stati Uniti d'America, vol. 78, pp. 27309-27331.
View web resources36
Carrara F., Falchi F., Amato G., Becarelli R., and Caldelli R. (2019) “Detecting adversarial inputs by looking in the black box”, ERCIM news, published by ERCIM., Le Chesnay, pp. 16-17.
View web resourcesView DOI resources37
Carvalho D. D., Ferreira D. R., Carvalho P. J., Imrisek M., Mlynar J., Fernandes H., and Contributors J. (2019) “Deep neural networks for plasma tomography with applications to JET and COMPASS”, Journal of instrumentation, published by Institute of Physics Publishing, Bristol, Regno Unito, vol. 14, pp. 1-6.
View DOI resources38
Cataliotti A., Cervellera C., Cosentino V., Di Cara D., Gaggero M., Macciò D., Marsala G., Ragusa A., and Tinè G. (2019) “An improved load flow method for MV networks based on LV load measurements and estimations”, IEEE transactions on instrumentation and measurement, published by Institute of Electrical and Electronics Engineers., New York, Stati Uniti d'America, vol. 68, pp. 430-438.
View web resourcesView DOI resources39
Cauteruccio F., Fortino G., Guerrieri A., Liotta A., Mocanu D. C., Perra C., Terracina G., and Torres V. M. (2019) “Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance”, Information fusion (Print), published by Elsevier Science, Tokyo, Paesi Bassi, vol. 52, pp. 13-30.
View DOI resources40
Chincarini M., Qiu L., Spinelli L., Torricelli A., Minero M., Dalla Costa E., Mariscoli M., Ferri N., Giammarco M., and Vignola G. (2019) “Evaluation of Sheep Anticipatory Response to a Food Reward by Means of Functional Near-Infrared Spectroscopy”, Animals (Basel), published by Molecular Diversity Preservation International, Basel, vol. 9.
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Cimini V., Gianani I., Spagnolo N., Leccese F., Sciarrino F., and Barbieri M. (2019) “Calibration of Quantum Sensors by Neural Networks”, Physical review letters, published by American Physical Society, College Park, MD, Stati Uniti d'America, vol. 123, pp. 230502-230502.
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Coccurello R. (2019) “Anhedonia in depression symptomatology: Appetite dysregulation and defective brain reward processing”, Behavioural brain research, published by Elsevier, Tokyo, Paesi Bassi, vol. 372.
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D'Acunto M., Martinelli M., and Moroni D. (2019) “From human mesenchymal stromal cells to osteosarcoma cells classification by deep learning”, Journal of intelligent & fuzzy systems, published by John Wiley & Sons, New York, NY, Stati Uniti d'America, vol. 37, pp. 7199-7206.
View web resourcesView DOI resources44
De Falco I., De Pietro G., Della Cioppa A., Sannino G., Scafuri U., and Tarantino E. (2019) “Evolution-based configuration optimization of a Deep Neural Network for the classification of Obstructive Sleep Apnea episodes”, Future generation computer systems, published by North-Holland, Amsterdam, Paesi Bassi, vol. 98, pp. 377-391.
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Delogu R. S., Montisci A., Pimazzoni A., Serianni G., and Sias G. (2019) “Neural network based prediction of heat flux profiles on STRIKE”, Fusion engineering and design, published by North Holland., Amsterdam, Paesi Bassi, vol. 146, pp. 2307-2313.
View DOI resources46
Falavigna G., Costantino G., Furlan R., Quinn J. V., Ungar A., and Ippoliti R. (2019) “Artificial neural networks and risk stratification in emergency departments”, Internal and emergency medicine (Testo stamp. ), published by CEPI, Roma, Italia, vol. 14, pp. 291-299.
View web resources47
Falchi F. (2019) “About deep learning, intuition and thinking”, ERCIM news, published by ERCIM., Le Chesnay, pp. 14-14.
View web resourcesView DOI resources48
Gargiulo F., Silvestri S., Ciampi M., and De Pietro G. (2019) “Deep neural network for hierarchical extreme multi-label text classification”, Applied soft computing (Print), published by Elsevier Science, [S. l. ], Paesi Bassi, vol. 79, pp. 125-138.
View DOI resources49
Ieracitano C., Mammone N., Bramanti A., Hussain A., and Morabito F. C. (2019) “A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 323, pp. 96-107.
View web resourcesView DOI resources50
Jalil B., Leone G. R., Martinelli M., Moroni M., Pascali M. A., and Berton A. (2019) “Fault detection in power equipment via an unmanned aerial system using multi modal data”, Sensors (Basel), ISSN 1424-8220, published by Molecular Diversity Preservation International (MDPI), Basel, vol. 19(13), 16 pages.
View web resourcesView DOI resources51
Kianoush S., Savazzi S., Rampa V., and Nicoli M. (2019) “People Counting by Dense WiFi MIMO Networks: Channel Features and Machine Learning Algorithms”, Sensors (Basel), published by Molecular Diversity Preservation International (MDPI), Basel, vol. 19.
View web resourcesView DOI resources52
Legnaioli S., Campanella B., Pagnotta S., Poggialini F., and Palleschi V. (2019) “Determination of Ash Content of coal by Laser-Induced Breakdown Spectroscopy”, Spectrochimica acta. Part B, Atomic spectroscopy, published by Pergamon, Oxford [etc. ], Regno Unito, vol. 155, pp. 123-126.
View web resourcesView DOI resources53
Lia A., Zonta M., Requie L. M., and Carmignoto G. (2019) “Dynamic interactions between GABAergic and astrocytic networks”, Neuroscience letters (Print), published by Elsevier Scientific Publishers Ireland, Amsterdam, Paesi Bassi, vol. 689, pp. 14-20.
View web resourcesView DOI resources54
Lu P., Chen P., Tian Y., He Y., Mo D., Yang R., Lasaponara R., and Masini N. (2019) “Reconstructing settlement evolution from neolithic to Shang dynasty in Songshan mountain area of central China based on self-organizing feature map”, Journal of cultural heritage, published by Elsevier, Paris, Francia, vol. 36, pp. 23-31.
View DOI resources55
Maj C., Azevedo T., Giansanti V., Borisov O., Dimitri G. M., Spasov S., Initiative A. D. N., Lió P., and Merelli I. (2019) “Integration of Machine Learning Methods to Dissect Genetically Imputed Transcriptomic Profiles in Alzheimer's Disease”, Frontiers in genetics, published by Frontiers Research Foundation, Lausanne, Svizzera, vol. 10.
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Martinez Manzanera O., Meles S., Leenders K., Renken R., Pagani M., Arnaldi D., Nobili F., Obeso J., Rodriguez O. M., Morbelli S., and Maurits N. (2019) “Scaled subprofile modeling and convolutional neural networks for the identification of Parkinson's disease in 3D nuclear imaging data”, International journal of neural systems, published by World Scientific., Singapore, Singapore.
View web resourcesView DOI resources57
Marzi C., Ferro M., and Pirrelli V. (2019) “A processing-oriented investigation of inflectional complexity”, Frontiers in communication, ISSN 2297-900X, published by Frontiers Media-Lausanne (Svizzera), vol. 4(48), pp. 1-23.
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Milella A., Marani R., Petitti A., and Reina G. (2019) “In-field high throughput grapevine phenotyping with a consumer-grade depth camera”, Computers and electronics in agriculture, published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 156, pp. 293-306.
View web resourcesView DOI resources59
Nigro S., Bordier C., I., Cerasa A., Nisticò R., Olivadese G., Vescio B., Bianco M. G., Fiorillo A., Barbagallo G., Crasà M., Quattrone A., Morelli M., Arabia G., Augimeri A., Nicolini C., Bifone A., G., Quattrone A., and H. (2019) “Apomorphine-induced reorganization of striato-frontal connectivity in patients with tremor-dominant Parkinson's disease”, Parkinsonism & related disorders, published by Elsevier Science, Oxford, Regno Unito, vol. 67, pp. 14-20.
View web resourcesView DOI resources60
Pagliuca P. and Nolfi S. (2019) “Robust optimization through neuroevolution”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 14, pp. 1-27.
View web resourcesView DOI resources61
Pota M., Marulli F., Esposito M., De Pietro G., and Fujita H. (2019) “Multilingual POS Tagging by a Composite Deep Architecture Based on Character-Level Features and On-the-Fly Calculation of Enriched Word Embeddings”, Knowledge-based systems, published by Butterworths, London, Regno Unito, vol. 164, pp. 309-323.
View web resourcesView DOI resources62
Roveda L., Haghshenas S., Caimmi M., Pedrocchi N., and Tosatti L. M. (2019) “Assisting Operators in Heavy Industrial Tasks: On the Design of an Optimized Cooperative Impedance Fuzzy-Controller With Embedded Safety Rules”, Frontiers in Robotics and AI, published by Mel Slater, Barcellona/Spagna, Svizzera, vol. 6.
View web resourcesView DOI resources63
Rundo L., Han C., Nagano Y., Zhang J., Hataya R., Militello C., Tangherloni A., Nobile M. S., Ferretti C., Besozzi D., Gilardi M. C., Vitabile S., Mauri G., Nakayama H., and Cazzaniga P. (2019) “USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 365, pp. 31-43.
View DOI resources64
Saccà V., Sarica A., Novellino F., Barone S., Tallarico T., Filippelli E., Granata A., Chiriaco C., Bossio R. B., Valentino P., and Quattrone A. (2019) “Evaluation of machine learning algorithms performance for the prediction of early multiple sclerosis from resting-state FMRI connectivity data”, Brain imaging and behavior (Print), published by Springer, New York, NY, Stati Uniti d'America, vol. 13, pp. 1103-1114.
View web resourcesView DOI resources65
Serani A., D'Agostino D., Campana E. F., and Diez M. (2019) “Assessing the Interplay of Shape and Physical Parameters by Unsupervised Nonlinear Dimensionality Reduction Methods”, Journal of ship research (Online), published by Society of Naval Architects and Marine Engineers, Jersey City, NJ, Stati Uniti d'America.
View web resourcesView DOI resources66
Staffa M., Giordano M., and Ficuciello F. (2019) “A WiSARD Network Approach for a BCI-Based Robotic Prosthetic Control”, International journal of social robotics (Print), published by Springer Netherlands, Dprdrecht, Paesi Bassi.
View web resourcesView DOI resources67
Tacchino F., Macchiavello C., Gerace D., and Bajoni D. (2019) “An artificial neuron implemented on an actual quantum processor”, NPJ Quantum Information, vol. 5, pp. 26-26.
View web resourcesView DOI resources68
Tarpanelli A., Santi E., Tourian M. J., Filippucci P., Amarnath G., and Brocca L. (2019) “Daily River Discharge Estimates by Merging Satellite Optical Sensors and Radar Altimetry Through Artificial Neural Network”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America.
View web resourcesView DOI resources69
Upreti D., Huang W., Kong W., Pascucci S., Pignatti S., Zhou X., Ye H., and Casa R. (2019) “A Comparison of Hybrid Machine Learning Algorithms for the Retrieval of Wheat Biophysical Variables from Sentinel-2”, Remote sensing (Basel), published by Molecular Diversity Preservation International, Basel, vol. 11, pp. Art. 481-1-Art. 481-22.
View web resourcesView DOI resources70
Zanotti C., Rotiroti M., Sterlacchini S., Cappellini G., Fumagalli L., Stefania G. A., Nannucci M. S., Leoni B., and Bonomi T. (2019) “Choosing between linear and nonlinear models and avoiding overfitting for short and long term groundwater level forecasting in a linear system”, Journal of hydrology (Amst. ), published by Elsevier, Oxford;, Paesi Bassi, vol. 578.
View web resourcesView DOI resources71
M. F. A. D. (2018) “Learning to Weight for Text Classification”, IEEE transactions on knowledge and data engineering (Online), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America.
72
Abbatangelo M., Núñez Carmona E., Sberveglieri V., Zappa D., Comini E., and Sberveglieri G. (2018) “Application of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of rind percentage of grated Parmigiano Reggiano”, Sensors (Basel), published by Molecular Diversity Preservation International (MDPI), Basel.
View web resourcesView DOI resources73
Amaral L. M. C. D., Barbieri S., Vila D., Puca S., Vulpiani G., Panegrossi G., Biscaro T., Sanò P., Petracca M., Marra A. C., Gosset M., and Dietrich S. (2018) “Assessment of Ground-Reference Data and Validation of the H-SAF Precipitation Products in Brazil”, Remote sensing, published by University of Wollongong., Wollongong, N. S. W., Australia, vol. 10, pp. 1-24.
View web resourcesView DOI resources74
Amato G., Falchi F., and Vadicamo L. (2018) “Aggregating binary local descriptors for image retrieval”, Multimedia tools and applications, published by Kluwer Academic Publishers, Dordrecht;, Stati Uniti d'America, vol. 77, pp. 5385-5415.
View web resourcesView DOI resources75
Battistoni S., Erokhin V., and Iannotta S. (2018) “Organic memristive devices for perceptron applications”, Journal of physics. D, Applied physics (Print), published by IOP Publishing, Bristol, Regno Unito, vol. 51.
View DOI resources76
Bhandari M. P., Carmona E. N., Abbatangelo M., Sberveglieri V., Duina G., Malla R., and Sberveglieri E. C. G. (2018) “Discrimination of Quality and Geographical Origin of Extra Virgin Olive Oil by S3 Device with Metal Oxides Gas Sensors”, Proceedings (MDPI), published by MDPI, Basel, Svizzera.
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Caleo M. and Restani L. (2018) “Exploiting botulinum neurotoxins for the study of brain physiology and pathology”, Toxins (Basel), published by MDPI, Basel, vol. 10.
View web resourcesView DOI resources78
Carrara F., Esuli A., Fagni T., Falchi F., and Moreo F. A. (2018) “Picture it in your mind: generating high level visual representations from textual descriptions”, Information retrieval (Boston), published by Kluwer Academic Publishers, Boston, Stati Uniti d'America, vol. 21, pp. 208-229.
View DOI resources79
Cervellera C. and Maccio D. (2018) “Distribution-Preserving Stratified Sampling for Learning Problems”, IEEE Transactions on Neural Networks and Learning Systems, published by Institute of Electrical and Electronics Engineers,-New York, NY, USA, Stati Uniti d'America, vol. 29, pp. 2886-2895.
View web resourcesView DOI resources80
Coro G., Gonzalez V. L., Magliozzi C., Ellenbroek A., Scarponi P., and Pagano P. (2018) “Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea”, Ecological modelling, published by Elsevier, Shannon;, Paesi Bassi, vol. 371, pp. 37-49.
View web resourcesView DOI resources81
Crisanti A. and Sompolinksy H. (2018) “Path integral approach to random neural networks”, Physical review. E (Print), published by American Physical Society, Ridge, NY, Stati Uniti d'America, vol. 98, pp. 062120-1-062120-16.
View DOI resources82
De Gregorio M. and Giordano M. (2018) “An experimental evaluation of weightless neural networks for multi-class classification”, Applied soft computing (Print), published by Elsevier Science, [S. l. ], Paesi Bassi, vol. 72, pp. 338-354.
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Di Gangi M., Lo Bosco G., and Rizzo R. (2018) “Deep learning architectures for prediction of nucleosome positioning from sequences data”, BMC bioinformatics, published by BioMed Central, [London], Regno Unito, vol. 19.
View web resourcesView DOI resources84
Ferro M., Marzi C., and Pirrelli V. (2018) “Discriminative word learning is sensitive to inflectional entropy”, Lingue e linguaggio, ISSN 1720-9331, published by Il Mulino, Bologna (Italia), vol. XVII(2), pp. 307-327.
View DOI resources85
Fiannaca A., La Paglia L., La Rosa M., Lo Bosco G., G Renda R. R., Gaglio S., and Urso A. (2018) “Deep learning models for bacteria taxonomic classification of metagenomic data”, BMC bioinformatics, published by BioMed Central, [London], Regno Unito, vol. 19, pp. 61-76.
View DOI resources86
Fici G., Langiu A., Lo Bosco G., and Rizzo R. (2018) “Bacteria classification using minimal absent words”, AIMS journal, published by AIMS, [London] ([16 Keyes Rd, Cricklewood, NW2 3XA), Regno Unito, vol. 5, pp. 23-32.
View web resourcesView DOI resources87
Gualtieri G., Carotenuto F., Finardi S., Tartaglia M., Toscano P., and Gioli B. (2018) “Forecasting PM10 hourly concentrations in northern Italy: Insights on models performance and PM10 drivers through self-organizing maps”, Atmospheric Pollution Research, published by Turkish National Committee for Air Pollution Research and Control, Istambul, Turchia.
View DOI resources88
Holroyd C. B., Ribas Fernandes J. J. F., Shahnazian D., Silvetti M., and Verguts T. (2018) “Human midcingulate cortex encodes distributed representations of task progress”, Proceedings of the National Academy of Sciences of the United States of America, published by The Academy, Washington, D. C., Stati Uniti d'America, vol. 115, pp. 6398-6403.
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Inack E. M., Santoro G. E., Dell'Anna L., and Pilati S. (2018) “Projective quantum Monte Carlo simulations guided by unrestricted neural network states”, Physical Review B, published by American Physical Society, Cambridge, MA, Stati Uniti d'America, vol. 98.
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Joutsensaari J., Ozon M., Nieminen T., Mikkonen S., Lahivaara T., Decesari S., Facchini M. C., Laaksonen A., and Lehtinen K. E. J. (2018) “Identification of new particle formation events with deep learning”, Atmospheric chemistry and physics (Online), published by Copernicus Publ., Göttingen, Germania, vol. 18, pp. 9597-9615.
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Lapkin D. A., Emelyanov A. V., Demin V. A., Berzina T. S., and Erokhin V. V. (2018) “Spike-timing-dependent plasticity of polyaniline-based memristive element”, Microelectronic engineering, published by North-Holland, Amsterdam, Paesi Bassi, vol. 185-186, pp. 43-47.
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Leo M., Carcagnì P., Distante C., Spagnolo P., Mazzeo P. L., Rosato A. C., Petrocchi S., Pellegrino C., Levante A., De Lumè F., and Lecciso F. (2018) “Computational Assessment of Facial Expression Production in ASD Children”, Sensors (Basel), published by Molecular Diversity Preservation International (MDPI), Basel, vol. 18.
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Lo Bosco G., Pilato G., and Schicchi D. (2018) “A Sentence based System for Measuring Syntax Complexity using a Recurrent Deep Neural Network”, CEUR workshop proceedings, published by M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen., Aachen, Germania, vol. 2244, pp. 95-101.
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Lo Bosco G., Pilato G., and Schicchi D. (2018) “A Neural Network model for the Evaluation of Text Complexity in Italian Language: a Representation Point of View”, Procedia computer science, published by Elsevier, Amsterdam, Paesi Bassi, vol. 145, pp. 464-470.
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M T. B. M. M. S. P. L. C. L. B. (2018) “How far are we from the use of satellite rainfall products in landslide forecasting?”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 210, pp. 65-75.
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Mannella F., Santucci V. G., Somogyi E., Jacquey L., O'Regan K. J., and Baldassarre G. (2018) “Know Your Body Through Intrinsic Goals”, Frontiers in neurorobotics, published by Frontiers Research Foundation, Lausanne, Svizzera, vol. 12.
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Mascanzoni E., Perego A., Marchi N., Scarabel L., Panozzo S., Ferrero A., Acutis M., and Sattin M. (2018) “Epidemiology and agronomic predictors of herbicide resistance in rice at a large scale”, Agronomy for sustainable development (Online), published by EDP sciences, Les Ulis, Francia.
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Pagliuca P., Milano N., and Nolfi S. (2018) “Maximizing adaptive power in neuroevolution”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 13.
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Palleschi A. and Palleschi V. (2018) “An Extended Kalman Filter approach to non-linear multivariate analysis of Laser-Induced Breakdown Spectroscopy spectra”, Spectrochimica acta. Part B, Atomic spectroscopy, published by Pergamon, Oxford [etc. ], Regno Unito, vol. 149, pp. 271-275.
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Paragliola G. and Coronato A. (2018) “Gait Anomaly Detection of Subjects with Parkinson?s Disease Using a Deep Time Series-based Approach”, IEEE access, published by Institute of Electrical and Electronics Engineers, Piscataway, NJ, Stati Uniti d'America.
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Passamonti L., Riccelli R., Lacquaniti F., Staab J. P., Indovina I., and G. (2018) “Brain responses to virtual reality visual motion stimulation are affected by neurotic personality traits in patients with persistent postural-perceptual dizziness”, Journal of vestibular research (Print), published by IOS Press, Amsterdam, Stati Uniti d'America, vol. 28, pp. 369-378.
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Pilozzi L., Farrelly F. A., Marcucci G., and Conti C. (2018) “Machine learning inverse problem for topological photonics”, Communications physics, published by Springer Nature, London, Regno Unito, vol. 1.
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Politi A., Ullner E., and Torcini A. (2018) “Collective irregular dynamics in balanced networks of leaky integrate-and-fire neurons”, The European physical journal. Special topics, published by Springer, Les Ulis;, Francia, vol. 227, pp. 1185-1204.
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Pota M., Marulli F., Esposito M., De Pietro G., and Fujita H. (2018) “Multilingual POS tagging by a composite deep architecture based on character-level features and on-the-fly enriched Word Embeddings”, Knowledge-based systems, published by Butterworths, London, Regno Unito.
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Quattrone A., Barbagallo G., Cerasa A., and Stoessl A. J. (2018) “Neurobiology of placebo effect in Parkinson's disease: What we have learned and where we are going”, Movement disorders, published by Raven Press, [New York, N. Y. ], Stati Uniti d'America, vol. 33, pp. 1213-1227.
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Reichenbach P., Rossi M., Malamud B., Mihir M., and Guzzetti F. (2018) “A review of statistically-based landslide susceptibility models”, Earth-science reviews, published by Elsevier, Oxford;, Paesi Bassi.
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Rivolta M. W., Aktaruzzamana M., Rizzo G., Lafortuna C. L., Ferrarin M., Bovi G., Bonardi D. R., Caspani A., and Sassi R. (2018) “Evaluation of the Tinetti score and fall risk assessment via accelerometry-based movement analysis”, Artificial intelligence in medicine (Print), published by Elsevier Science Publishers, Tecklenburg, Paesi Bassi, vol. 95, pp. 38-47.
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Rojas C., Tedesco M., Massobrio P., Marino A., Ciofani G., Martinoia S., and Raiteri R. (2018) “Acoustic stimulation can induce a selective neural network response mediated by piezoelectric nanoparticles”, Journal of neural engineering (Print), published by Institute of Physics Publishing, Bristol, Regno Unito, vol. 15.
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Rucco M., Giannini F., Lupinetti K., and Monti M. (2018) “A methodology for part classification with supervised machine learning”, Artificial intelligence for engineering design, analysis and manufacturing, published by Academic Press, San Diego, Regno Unito, pp. 1-14.
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Ruggeri M., Moroni S., and Holzmann M. (2018) “Nonlinear Network Description for Many-Body Quantum Systems in Continuous Space”, Physical review letters (Print), published by American Physical Society., [Woodbury, N. Y., etc. ], Stati Uniti d'America.
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Sammartino M., Marullo S., Santoleri R., and Scardi M. (2018) “Modelling the Vertical Distribution of Phytoplankton Biomass in the Mediterranean Sea from Satellite Data: A Neural Network Approach”, Remote sensing (Basel), published by Molecular Diversity Preservation International, Basel, vol. 10.
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Sano P., Panegrossi G., Casella D., Marra A. C., D'Adderio L. P., Rysman J. F., and Dietrich S. (2018) “The Passive Microwave Neural Network Precipitation Retrieval (PNPR) Algorithm for the CONICAL Scanning Global Microwave Imager (GMI) Radiometer”, Remote sensing (Basel), published by Molecular Diversity Preservation International, Basel, vol. 10.
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Santi E., Paloscia S., Pettinato S., Brocca L., Ciabatta L., and Entekhabi D. (2018) “On the synergy of SMAP, AMSR2 AND SENTINEL-1 for retrieving soil moisture”, International journal of applied earth observation and geoinformation, published by International Institute for Aerial Survey and Earth Sciences, Enschede, vol. 65, pp. 114-123.
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Sanyal A., Kumar P., Kar P., Chawla S., and Sebastiani F. (2018) “Optimizing non-decomposable measures with deep networks”, Machine learning, published by Kluwer Academic Publishers, Boston/U. S. A., Stati Uniti d'America, vol. 107, pp. 1597-1620.
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Shao W., Luo H., Zhao F., Ma Y., Zhao Z., and Crivello A. (2018) “Indoor positioning based on fingerprint-image and deep learning”, IEEE access, published by Institute of Electrical and Electronics Engineers, Piscataway, NJ, Stati Uniti d'America, vol. 6, pp. 74699-74712.
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Siano D. and Panza M. A. (2018) “Diagnostic method by using vibration analysis for pump fault detection”, Energy procedia (Online), published by Elsevier, Amsterdam, Paesi Bassi, vol. 148, pp. 10-17.
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Siano D., Panza M. A., and Badan J. P. (2018) “Prediction of Interior Vehicle Noise by Means of NARX Neural Networks”, SAE technical paper series, published by Society of Automotive Engineers, Warrendale, Penn., Stati Uniti d'America.
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Zappacosta S., Mannella F., Mirolli M., and Baldassarre G. (2018) “General differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain”, PLOS computational biology (Online), published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 14.
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Alcasena F. J., Salis M., Ager A. A., Castell R., and Vega Garcia C. (2017) “AssessingWildland Fire Risk Transmission to Communities in Northern Spain”, Forests, published by MDPI, Basel, vol. 8.
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Allocca L., Montanaro A., Amoresano A., Langella G., Niola V., and Quaremba G. (2017) “Chaos Theory Approach as Advanced Technique for GDI Spray Analysis”, SAE technical paper series, published by Society of Automotive Engineers, Warrendale, Penn., Stati Uniti d'America.
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Alloisio S., Garbati P., Viti F., Dante S., Barbieri R., Arnaldi G., Petrelli A., Gigoni A., Giannoni P., Quarto R., Nobile M., Vassalli M., and Pagano A. (2017) “Generation of a Functional Human Neural Network by NDM29 Overexpression in Neuroblastoma Cancer Cells”, Molecular neurobiology, published by Humana Press, Clifton, NJ, Stati Uniti d'America, vol. 54, pp. 6097-6106.
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Amato G., Carrara F., Falchi F., Gennaro C., Meghini C., and Vairo C. (2017) “Deep learning for decentralized parking lot occupancy detection”, Expert systems with applications, published by Pergamon, Oxford, Regno Unito, vol. 72, pp. 327-334.
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Amendola S., Maimone F., Pasini A., Ciciulla F., and Pelino V. (2017) “A neural network ensemble downscaling system (SIBILLA) for seasonal forecasts over Italy: winter case studies”, Meteorological applications (Print), published by Royal Meteorological Society, Reading, Regno Unito, vol. 24, pp. 157-166.
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Angulo Garcia D., Luccioli S., Olmi S., and Torcini A. (2017) “Death and rebirth of neural activity in sparse inhibitory networks”, New journal of physics, published by Deutsche Physikalische Gesellschaft., [Bristol], Regno Unito, vol. 19.
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Apicella I., Scarpetta S., and De Candia A. (2017) “Cortical phase transitions as an effect of topology of neural network”, Smart innovation, systems and technologies (Internet), published by Heidelberg, [Berlin], Germania, vol. 69, pp. 85-96.
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Bacciu D., Chessa S., Gallicchio C., Micheli A., Pedrelli L., Ferro E., Fortunati L., La Rosa D., Palumbo F., Vozzi F., and Parodi O. (2017) “A learning system for automatic Berg Balance Scale score estimation”, Engineering applications of artificial intelligence, ISSN 0952-1976, published by Pineridge, Swansea (Regno Unito), vol. 66, pp. 60-74.
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Baldassarre G., Santucci V. G., Cartoni E., and Caligiore D. (2017) “The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction”, Behavioral and brain sciences (Online), published by Cambridge University Press., Cambridge, Regno Unito, vol. 40.
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Battistoni S., Erokhin V., and Iannotta S. (2017) “Emulation with Organic Memristive Devices of Impairment of LTP Mechanism in Neurodegenerative Disease Pathology”, Neural Plasticity (Print), published by Hindawi Publishing Corporation, Cairo, Egitto.
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Bertolaccini L., Solli P., Pardolesi A., and Pasini A. (2017) “An overview of the use of artificial neural networks in lung cancer research”, Journal of thoracic disease (Print), published by Pioneer Bioscience Publishing Company, Hong Kong, Hong Kong, vol. 9, pp. 924-931.
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Bertolotti E., Burioni R., Di Volo M., and Vezzani A. (2017) “Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity”, Physical review. E (Print), published by American Physical Society, Ridge, NY, Stati Uniti d'America, vol. 95.
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Cavallo D. P., Cefola M., Pace B., Logrieco A. F., and Attolico G. (2017) “Non-destructive automatic quality evaluation of fresh-cut iceberg lettuce through packaging material”, Journal of food engineering, published by Applied Science Publishers., London, Regno Unito.
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Cerasa A., Sarica A., Martino I., Fabbricatore C., Tomaiuolo F., Rocca F., Caracciolo M., and Quattrone A. (2017) “Increased cerebellar gray matter volume in head chefs”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 12, e0171457 pages.
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Ciabatta L., Marra A. C., Panegrossi G., Casella D., Sano P., Dietrich S., Massari C., and Brocca L. (2017) “Daily precipitation estimation through different microwave sensors: Verification study over Italy”, Journal of hydrology (Amst. ), published by Elsevier, Oxford;, Paesi Bassi, vol. 545, pp. 436-450.
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Costantino G., Falavigna G., Solbiati M., Casagranda I., Sun B. C., Grossman S. A., Quinn J. V., Reed M. J., Ungar A., Montano N., Furlan R., and Ippoliti R. (2017) “Neural networks as a tool to predict syncope risk in the Emergency Department”, Europace (Lond. Engl. ), published by W. B. Saunders, Philadelphia, Regno Unito, vol. 19, pp. 1891-1895.
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Craglia M., Hradec J., Nativi S., and Santoro M. (2017) “Exploring the depths of the global earth observation system of systems”, Big earth data (Online), published by Taylor & Francis, [Abingdon], Regno Unito, vol. 1, pp. 21-46.
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De Gregorio M. and Giordano M. (2017) “Background estimation by weightless neural networks”, Pattern recognition letters, published by North-Holland, Amsterdam, Paesi Bassi, vol. 96, pp. 55-65.
137
Del Coco M., Carcagnì P., Leo M., Spagnolo P., Mazzeo P. L., and Distante C. (2017) “Multi-branch CNN for Multi-scale Age Estimation”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 10590, pp. 234-244.
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Di Piazza M. C., La Tona G., Luna M., and Di Piazza A. (2017) “A two-stage Energy Management System for smart buildings reducing the impact of demand uncertainty”, Energy and buildings, published by Elsevier, Lausanne;, Paesi Bassi, vol. 139, pp. 1-9.
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Di Piazza M. C., Luna M., and Pucci M. (2017) “Electrical Loss Minimization Technique for Wind Generators based on a Comprehensive Dynamic Modelling of Induction Machines”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. PP.
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Falcini F., Lami G., and Mitidieri A. C. (2017) “Deep Learning in Automotive Software”, IEEE software, published by IEEE Computer Society, [Los Alamitos, CA, Stati Uniti d'America, vol. 34, pp. 56-63.
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Fiannaca A., La Rosa M., La Paglia L., Rizzo R., and Urso A. (2017) “NRC: Non-coding RNA Classifier based on structural features”, BioData mining, published by BioMed Central, [London], Regno Unito, vol. 10.
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Karakus O., Kuruoglu E. E., and Altinkaya M. A. (2017) “One-day ahead wind speed/power prediction based on polynomial autoregressive model”, IET renewable power generation (Print), published by IET, Stevenage, Regno Unito, vol. 11, pp. 1430-1439.
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Maksimenko V. A., Luttjohann A., Makarov V. V., Goremyko M. V., Koronovskii A. A., Nedaivozov V., Runnova A. E., Van Luijtelaar G., Hramov A. E., and Boccaletti S. (2017) “Macroscopic and microscopic spectral properties of brain networks during local and global synchronization”, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, published by Published by the American Physical Society through the American Institute of Physics, New York, N. Y., Stati Uniti d'America, vol. 96, pp. 012316-1-012316-10.
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Mazzocchi F. and Pasini A. (2017) “Climate model pluralism beyond dynamical ensembles”, Wiley interdisciplinary reviews. Climate change (Online), published by John Wiley & Sons, [Hoboken, NJ], Stati Uniti d'America, vol. 8.
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Modarres M. H., Aversa R., Cozzini S., Cozzini S., Ciancio R., Leto A., and Brandino G. P. (2017) “Neural Network for Nanoscience Scanning Electron Microscope Image Recognition”, Scientific reports (Nature Publishing Group), published by Nature Publishing Group, London, Regno Unito, vol. 7.
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Montanaro A., Allocca L., Amoresano A., and Langella G. (2017) “A "dynamic System" Approach for the Experimental Characterization of a Multi-Hole Spray”, SAE technical paper series, published by Society of Automotive Engineers, Warrendale, Penn., Stati Uniti d'America.
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Pagnotta S., Lezzerini M., Ripoll Seguer L., Hidalgo M., Grifoni E., Legnaioli S., Lorenzetti G., Poggialini F., and Palleschi V. (2017) “Micro-Laser-Induced Breakdown Spectroscopy (Micro-LIBS) Study on Ancient Roman Mortars”, Applied spectroscopy, published by Society for Applied Spectroscopy., [Baltimore, Md. ], Stati Uniti d'America, vol. 71, pp. 721-727.
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Palmeri M., Vella F., Infantino I., and Gaglio S. (2017) “Sign Languages Recognition Based on Neural Network Architecture”, Smart innovation, systems and technologies (Print), published by Heidelberg, Heidelberg;, Germania, pp. 109-118.
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Pasini A., Racca P., Amendola S., Cartocci G., and Cassardo C. (2017) “Attribution of recent temperature behaviour reassessed by a neural-network method”, Scientific reports (Nature Publishing Group), published by Nature Publishing Group, London, Regno Unito, vol. 7.
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Pierotti L., Gherardi F., Facca G., Piccardi L., and Moratti G. (2017) “Detecting CO2 anomalies in a spring on Mt. Amiata volcano (Italy)”, Physics and chemistry of the earth. Parts A/B/C (Online), published by Elsevier Science, [New York], Paesi Bassi, vol. 98, pp. 161-172.
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Pittorino F., Ibanez Berganza M., Di Volo M., Vezzani A., and Burioni R. (2017) “Chaos and Correlated Avalanches in Excitatory Neural Networks with Synaptic Plasticity”, Physical review letters, published by American Physical Society, College Park, MD, Stati Uniti d'America, vol. 118.
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Santi E., Paloscia S., Pampaloni P., Pettinato S., Nomaki T., Seki M., Sekiya K., and Maeda T. (2017) “Vegetation Water Content Retrieval by Means of Multifrequency Microwave Acquisitions From AMSR2”, IEEE journal of selected topics in applied earth observations and remote sensing (Print), published by IEEE, Piscataway, N. J., Stati Uniti d'America, vol. 10, pp. 3861-3873.
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Santi E., Paloscia S., Pettinato S., Fontanelli G., Mura M., Zolli C., Maselli F., Chiesi M., Bottai L., and Chirici G. (2017) “The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 200, pp. 63-73.
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Silvestro P. C., Pignatti S., Pascucci S., Yang H., Li Z., Yang G., Huang W., and Casa R. (2017) “Estimating Wheat Yield in China at the Field and District Scale from the Assimilation of Satellite Data into the Aquacrop and Simple Algorithm for Yield (SAFY) Models”, Remote sensing (Basel), published by Molecular Diversity Preservation International, Basel, vol. 9.
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Taglialatela F., Lavorgna M., Di Iorio S., Mancaruso E., and Vaglieco B. M. (2017) “Real Time Prediction of Particle Sizing at the Exhaust of a Diesel Engine by Using a Neural Network Model”, SAE International journal of engines (Print), published by SAE International, Warrendale, PA, Stati Uniti d'America, vol. 10.
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Tartarisco G., Tonacci A., Minciullo P. L., Billeci L., Pioggia G., Incorvaia C., and Gangemi S. (2017) “The soft computing-based approach to investigate allergic diseases: a systematic review”, Clinical and molecular allergy (Online), ISSN 1476-7961, published by BioMed Central, London (Regno Unito), vol. 15, 14 pages.
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Tateo A., Miglietta M., Fedele F., Menegotto M., Monaco A., and Bellotti R. (2017) “Ensemble using different Planetary Boundary Layer schemes in WRF model for wind speed and direction prediction over Apulia region”, Advances in science and research (Print), published by Copernicus Publ., Göttingen, Germania, vol. 14, pp. 95-102.
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Tomaselli V., De Vincenzi M., Fasciano C., Materassi A., Veronico G., Paffetti D., and Vettori C. (2017) “Analysing phenological features in natural and semi-natural environments next to cultivated fields as a prerequisite for potential pollen flow evaluation”, Italian journal of agrometeorology, published by AIM: Milano, [poi] Patron Granarolo dell'Emilia, Bologna, Italia, vol. 2017, pp. 25-36.
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Tosun E., Aydin K., Merola S. S., and Irimescu A. (2017) “ESTIMATION OF OPERATIONAL PARAMETERS FOR A DIRECT INJECTION TURBOCHARGED SPARK IGNITION ENGINE BY USING REGRESSION ANALYSIS AND ARTIFICIAL NEURAL NETWORK”, Thermal science, published by Vinca Institute of Nuclear Sciences, Belgrade, Serbia, vol. 21, pp. 401-412.
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Vasanelli E., Colangiuli D., Calia A., Sbartaï Z. M., and Breysse D. (2017) “Combining non-invasive techniques for reliable prediction of soft stone strength in historic masonries”, Construction & building materials, published by Scientific & Technical Press, Reigate, Regno Unito, vol. 146, pp. 744-754.
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Wandera L., Mallick K., Kiely G., Roupsard O., Peichl M., and Magliulo V. (2017) “Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: an Artificial Neural Network approach”, Hydrology and earth system sciences, published by Copernicus Publ., Göttingen, Germania, vol. 21, pp. 197-215.
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Amato G., Falchi F., and Vadicamo L. (2016) “Visual Recognition of Ancient Inscriptions Using Convolutional Neural Network and Fisher Vector”, ACM journal on computing and cultural heritage (Print), published by Association for Computing Machinery, New York, NY, Stati Uniti d'America, vol. 9, pp. 21-24.
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Andre J. and Nolfi S. (2016) “Evolutionary robotics simulations help explain why reciprocity is rare in nature”, Scientific reports (Nature Publishing Group), published by Nature Publishing Group, London, Regno Unito, vol. 6, pp. 1-7.
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Auriemma M. and Iazzetta A. (2016) “Viscosity of Alumina Water-Based Nanofluids Modeling by Artificial Neural Network”, Indian journal of science and technology (Print), published by Indian Society for Education and Environment, Chennai, India, vol. 9.
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Barbuti R., Chessa S., Micheli A., and Pucci R. (2016) “Localizing tortoise nests by neural networks”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 11.
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Basile M., Valerio F., Balestrieri R., Posillico M., Bucci R., Altea T., De Cinti B., and Matteucci G. (2016) “Patchiness of forest landscape can predict species distribution better than abundance: The case of a forest-dwelling passerine, the short-toed treecreeper, in central Italy”, PeerJ, vol. 2016.
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Bonacini E., Burioni R., Di Volo M., Groppi M., Soresina C., and Vezzani A. (2016) “How single node dynamics enhances synchronization in neural networks with electrical coupling”, Chaos, solitons and fractals, published by Pergamon., Oxford, Regno Unito, vol. 85, pp. 32-43.
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Borrotti M., Pievatolo A., Critelli I., Degiorgi A., and Colledani M. (2016) “A computer-aided methodology for the optimization of electrostatic separation processes in recycling”, Applied stochastic models in business and industry (Print), published by John Wiley & Sons, Chichester, Regno Unito, vol. 32, pp. 133-148.
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Caligiore D., Mustile M., Spalletta G., and Baldassarre G. (2016) “Action observation and motor imagery for rehabilitation in Parkinson's disease: A systematic review and an integrative hypothesis”, Neuroscience and biobehavioral reviews, published by Pergamon., New York, Stati Uniti d'America, vol. 72, pp. 210-222.
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Capitano F., Gargiuli C., Angerilli A., Maccaroni K., Pelliccia F., Mele A., and Camilloni G. (2016) “RNA polymerase i transcription is modulated by spatial learning in different brain regions”, Journal of neurochemistry, published by Blackwell, Oxford, Regno Unito, vol. 136, pp. 706-716.
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Casagranda I., Costantino G., Falavigna G., Furlan R., and Ippoliti R. (2016) “Artificial Neural Networks and risk stratification models inEmergency Departments: The policy maker's perspective”, Health policy (Amst. Print), published by Elsevier, Amsterdam, Paesi Bassi, vol. 120, pp. 111-119.
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Caviglione L., Gaggero M., Lalande J., Mazurczyk W., and Urbanski M. (2016) “Seeing the unseen: revealing mobile malware hidden communications via energy consumption and artificial intelligence”, IEEE transactions on information forensics and security, published by IEEE, New York, N. Y., Stati Uniti d'America, vol. 11, pp. 799-810.
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De Gregorio M. and Giordano M. (2016) “Cloning DRASiW systems via memory transfer”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 192, pp. 115-127.
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De Gregorio M., Giordano M., Rossi S., and Staffa M. (2016) “Experimenting WNN support in object tracking systems”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 183, pp. 79-89.
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Di Volo M., Burioni R., Casartelli M., Livi R., and Vezzani A. (2016) “Neural networks with excitatory and inhibitory components: Direct and inverse problems by a mean-field approach”, Physical review. E, Statistical, nonlinear and soft matter physics (Online), published by Published by the American Physical Society through the American Institute of Physics, Melville, N. Y., Stati Uniti d'America, vol. 93, 012305 pages.
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Emelyanov A. V., Lapkin D. A., Demin V. A., Erokhin V. V., Battistoni S., Baldi G., Dimonte A., Korovin A. N., Iannotta S., Kashkarov P. K., and Kovalchuk M. V. (2016) “First steps towards the realization of a double layer perceptron based on organic memristive devices”, AIP advances, published by American Institute of Physics, Melville, NY, Stati Uniti d'America, vol. 6, pp. 111301-1.
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Garcia G., Brogioni M., Venturini V., Rodriguez L., Fontanelli G., Walker E., Graciani S., and Macelloni G. (2016) “Soil moisture estimation using multi linear regression with terraSAR-X data [Determinaci?n de la humedad de suelo mediante regresion lineal multiple con datos TerraSAR-X]”, Revista de teledetección, published by Asociación Española de Teledetección., Madrid, Spagna, vol. 2016, pp. 73-81.
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Heibati B., Rodriguez Couto S., Ozgonenel O., Turan N. G., Aluigi A., Zazouli M. A., Ghozikali M. G., Mohammadyan M., and Albadarin A. B. (2016) “A modeling study by artificial neural network on ethidium bromide adsorption optimization using natural pumice and iron-coated pumice”, Desalination and water treatment (Print), published by Balaban Publishers, Hopkinton, MA, Stati Uniti d'America, vol. 57, pp. 13472-13483.
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Juarez Hernandez L. J., Cornella N., Pasquardini L., Battistoni S., Vidalino L., Vanzetti L., Caponi S., Serra M. D., Iannotta S., Pederzolli C., Macchi P., and Musio C. (2016) “Bio-hybrid interfaces to study neuromorphic functionalities: New multidisciplinary evidences of cell viability on poly(anyline) (PANI), a semiconductor polymer with memristive properties”, Biophysical chemistry (Print), published by Elsevier, New York;, Paesi Bassi, vol. 208, pp. 40-47.
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Langella G., Basile A., Bonfante A., Mileti F. A., and Terribile F. (2016) “Spatial analysis of clay content in soils using neurocomputing and pedological support: a case study of Valle Telesina (South Italy)”, Environmental earth sciences (Internet), published by Springer, Berlin, Germania, vol. 75, pp. 1-19.
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Liu Y., Weisberg R., Vignudelli S., and Mitchum G. (2016) “Patterns of the loop current system and regions of sea surface height variability in the eastern Gulf of Mexico revealed by the self-organizing maps”, Journal of geophysical research. Oceans (Print), published by Wiley Subscription Services, Hoboken, Stati Uniti d'America, vol. 121, pp. 2347-2366.
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Mameli O., Marcello ·., Caria A., Rosalia ·., Pellitteri ·., Russo A., Salvatore ·., Saccone ·., and Stanzani S. (2016) “Evidence for a trigeminal mesencephalic-hypoglossal nuclei loop involved in controlling vibrissae movements in the rat”, Experimental brain research, published by Springer, Berlin, Germania, vol. 234, pp. 753-761.
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Maniscalco U. and Rizzo R. (2016) “A virtual layer of measure based on soft sensors”, Journal of Ambient Intelligence and Humanized Computing, published by springer, itali, Germania, pp. 1-10.
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Moroni D., Pieri G., Salvetti O., Tampucci M., Domenici C., and Tonacci A. (2016) “Sensorized buoy for oil spill early detection”, Methods in oceanography (Online), ISSN 2211-1239, published by Elsevier (Paesi Bassi), vol. 17, pp. 221-231.
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Nigro S., Riccelli R., Passamonti L., Arabia G., Morelli M., Nisticò R., Novellino F., Salsone M., Barbagallo G., and Quattrone A. (2016) “Characterizing structural neural networks in de novo Parkinson disease patients using diffusion tensor imaging”, Human brain mapping (Online), published by Wiley-Liss, Inc., [New York, N. Y. ], Stati Uniti d'America, vol. 37, pp. 4500-4510.
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Nucci C. G., De Bonis P., Mangiola A., Santini P., Sciandrone M., Risi A., and Anile C. (2016) “Intracranial pressure wave morphological classification: automated analysis and clinical validation”, Acta neurochirurgica, published by Springer, Wien;, Austria, vol. 158, pp. 581-588.
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Palumbo F., Gallicchio C., Pucci R., and Micheli A. (2016) “Human activity recognition using multisensor data fusion based on Reservoir Computing”, Journal of ambient intelligence and smart environments (Print), published by IOS Press, Amsterdam, Paesi Bassi, vol. 8, pp. 87-107.
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Panegrossi G., Casella D., Dietrich S., Marra A. C., Sanò P., Mugnai A., Baldini L., Roberto N., Adirosi E., Cremonini R., Bechini R., Vulpiani G., Petracca M., and Porcù F. (2016) “Use of the GPM Constellation for Monitoring Heavy Precipitation Events Over the Mediterranean Region”, IEEE journal of selected topics in applied earth observations and remote sensing (Online), published by Institute of Electrical and Electronics Engineers, Inc., New York, N. Y., Stati Uniti d'America.
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Parodi S., Manneschi C., Verda D., Ferrari E., and Muselli M. (2016) “Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables”, Health informatics journal (Online), published by Sage Publications., London, Regno Unito, pp. 1-12.
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Puyana Romero V., Maffei L., Brambilla G., and Ciaburro G. (2016) “Modelling the soundscape quality of urban waterfronts by artificial neural networks”, Applied acoustics, published by Applied Science Publishers, Barking, Regno Unito, vol. 111, pp. 121-128.
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Puyana R. V., Maffei L., Brambilla G., and Ciaburro G. (2016) “Acoustic, visual and spatial indicators for the description of the soundscape of waterfront areas with and without road traffic flow”, International journal of environmental research and public health (Print), published by MDPI, Basel, vol. 13, pp. 1-19.
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Quaremba G., Allocca L., Amoresano A., Niola V., and Langella A. M. G. (2016) “Fuzzy logic approach to GDI spray characterization”, SAE technical paper series, published by Society of Automotive Engineers, Warrendale, Penn., Stati Uniti d'America.
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Russo T., Carpentieri P., Fiorentino F., Arneri E., Scardi M., Cioffi A., and Cataudella S. (2016) “Modeling landings profiles of fishing vessels: An application of Self-Organizing Maps to VMS and logbook data”, Fisheries research, published by Elsevier, Amsterdam, Paesi Bassi, vol. 181, pp. 34-47.
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Sanò P., Panegrossi G., Casella D., Marra A. C., Di Paola F., and Dietrich S. (2016) “The new Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for the cross-track scanning ATMS radiometer: Description and verification study over Europe and Africa using GPM and TRMM spaceborne radars”, Atmospheric measurement techniques (Print), published by Copernicus Publications, Göttingen, Germania, vol. 9, pp. 5441-5460.
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Santi E., Paloscia S., Pettinato S., Brocca L., and Ciabatta L. (2016) “Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture from AMSR-E Data in Central Italy”, IEEE journal of selected topics in applied earth observations and remote sensing (Print), published by IEEE, Piscataway, N. J., Stati Uniti d'America, vol. 9, pp. 2478-2492.
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Simione L. and Nolfi S. (2016) “The Emergence of Selective Attention through Probabilistic Associations between Stimuli and Actions”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 11.
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Vasta R., Augimeri A., Cerasa A., Nigro S., Gramigna V., Nonnis M., Rocca F., Zito G., and Quattrone A. (2016) “Hippocampal subfield atrophies in converted and not-converted mild cognitive impairments patients by a Markov random fields algorithm”, Current Alzheimer research (Print), published by Bentham Science Publishers, Hilversum, Paesi Bassi, vol. 13, pp. 566-574.
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Vozzi F., Fortunati L., Gallicchio C., Palumbo F., Pedrelli L., Micheli A., Ferro E., Lanzisera S., Carotenuto F., Illario M., and Parodi O. (2016) “ICT solution for balance assessment in elderly: the DOREMI system validation and applicability”, European geriatric medicine (Print), ISSN 1878-7649, published by Elsevier-Amsterdam (Paesi Bassi), vol. 7(1), pp. 750-751.
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Wandera L., Mallick K., Kiely G., Roupsard O., Peichl M., and Magliulo V. (2016) “Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: an Artificial Neural Network approach”, Hydrology and earth system sciences, published by Copernicus Publ., Göttingen, Germania.
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Angulo Garcia D. and Torcini A. (2015) “Stochastic mean-field formulation of the dynamics of diluted neural networks”, Physical review. E, Statistical, nonlinear, and soft matter physics (Print), published by Published by the American Physical Society through the American Institute of Physics, Melville, NY, Stati Uniti d'America, vol. 91, pp. 022928-1-022928-12.
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Basile A., Curcio S., Bagnato G., Liguori S., Jokar S. M., and Iulianelli A. (2015) “Water gas shift reaction in membrane reactors: Theoretical investigation by artificial neural networks model and experimental validation”, International journal of hydrogen energy, published by Pergamon Press., New York, Regno Unito, vol. 40, pp. 5897-5906.
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Bertolaccini L., Viti A., Boschetto L., Pasini A., Attanasio A., Terzi A., and Cassardo C. (2015) “Analysis of spontaneous pneumothorax in the city of Cuneo: environmental correlations with meteorological and air pollutant variables”, Surgery today (Print), published by Springer., Tokyo, Giappone, vol. 45, pp. 625-629.
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Bizon K., Continillo G., Mancaruso E., and Vaglieco B. M. (2015) “Application of RBF neural networks for real-time pressure prediction in a diesel engine”, International Journal of Engineering & Technology, published by Science Publishing Corporation, vol. 4, pp. 497-508.
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Brilli F. G. B., Fares S., Zenone T., Zona D., Gielen B., Loreto F. J. I., and Ceulemans R. (2015) “Rapid leaf development drives the seasonal pattern of volatile organic compound (VOC) fluxes in a 'coppiced' bioenergy poplar plantation”, Plant, cell and environment (Print), published by Blackwell Scientific, Oxford, Regno Unito.
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Calabretta R. and Neirotti J. P. (2015) “Adaptive Agents in Changing Environments, the Role of Modularity”, Neural Processing Letters, published by D facto s. a., Bruxelles, Belgio, vol. 42, pp. 257-274.
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Calluso C., Tosoni A., Pezzulo G., Spadone S., and Committeri G. (2015) “Interindividual Variability in Functional Connectivity as Long-Term Correlate of Temporal Discounting”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 10.
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Cerasa A., Donzuso G., Morelli M., Mangone G., Salsone M., Passamonti L., Augimeri A., Arabia G., and Quattrone A. (2015) “The motor inhibition system in Parkinson's disease with levodopa-induced dyskinesias”, Movement disorders (Online), published by John Wiley & Sons, New York, N. Y., Stati Uniti d'America, vol. 30, pp. 1912-1920.
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Cerasa A., Koch G., Donzuso G., Mangone G., Morelli M., Brusa L., Bassi M. S., Ponzo V., Picazio S., Passamonti L., Salsone M., Augimeri A., Caltagirone C., and Quattrone A. (2015) “A network centred on the inferior frontal cortex is critically involved in levodopa-induced dyskinesias”, Brain (Online), published by Oxford University Press, Oxford, Regno Unito, vol. 138, pp. 414-427.
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Cicirelli G., Attolico C., Guaragnella C., and D'Orazio T. (2015) “A kinect-based gesture recognition approach for a natural human robot interface”, International journal of advanced robotic systems (Print), published by Institute for Production Engineering. Intelligent Manufacturing Systems. Vienna University of Technology., Wien, Austria, vol. 12.
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Coro G., Magliozzi C., Ellenbroek A., and Pagano P. (2015) “Improving data quality to build a robust distribution model for Architeuthis dux”, Ecological modelling, published by Elsevier, Shannon;, Paesi Bassi, vol. 305, pp. 29-39.
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D'Angella A., Nisio S., and Ciotoli G. (2015) “Applicazione di analisi statistica multivariata, Rete Neurale Artificiale e metodo euristico per la valutazione della suscettibilità da sinkhole nella piana di S. Vittorino (RI)”, Memorie descrittive della carta geologica d'Italia, published by Servizio geologico d'Italia., Roma, Italia, vol. XCIX, pp. 239-254.
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Davoli F. and Mongelli M. (2015) “Neural Approximations of Analog Joint Source-Channel Coding”, IEEE signal processing letters, published by IEEE Signal Processing Society, New York, NY, Stati Uniti d'America, vol. 22, pp. 421-425.
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Del Frate F., Fabrini I., Fiumi L., and Tocci S. (2015) “Analysis of the soil sealing in the urban area of Rome through automatic processing of satellite data with neural networks”, Applied geomatics (Print), published by Springer, Heidelberg, Germania, vol. 7.
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Del Moro G., Barca E., De Sanctis M., Mascolo G., and Di Iaconi C. (2015) “Gross parameters prediction of a granular-attached biomass reactor by means of multi-objective genetic-designed artificial neural networks: touristic pressure management case”, Environmental science and pollution research international, published by Springer, Berlin, Germania.
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Demin V. A., Erokhin V. V., Emelyanov A. V., Battistoni S., Baldi G., Iannotta S., Kashkarov P. K., and Kovalchuk M. V. (2015) “Hardware elementary perceptron based on polyaniline memristive devices”, Organic electronics (Print), published by North-Holland:, Amsterdam, Paesi Bassi, vol. 25, pp. 16-20.
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Di Piazza M. C. and Pucci M. (2015) “Induction Machines based Wind Generators with Neural Maximum Power Point Tracking and Minimum Losses Techniques”, IEEE transactions on industrial electronics (1982. Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. PP.
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Donnarumma F., Murano A., and Prevete R. (2015) “Dynamic Network Functional Comparison via Approximate-bisimulation”, Control and Cybernetics, published by Panstwowe Wydawnictwo Naukowe., Warszawa, Polonia, vol. 44, pp. 99-127.
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Donnarumma F., Prevete R., Chersi F., and Pezzulo G. (2015) “A Programmer-Interpreter Neural Network Architecture for Prefrontal Cognitive Control”, International journal of neural systems, published by World Scientific., Singapore, Singapore, vol. 25.
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Donnarumma F., Prevete R., De Giorgio A., Montone G., and Pezzulo G. (2015) “Learning programs is better than learning dynamics: A programmable neural network hierarchical architecture in a multi-task scenario”, Adaptive behavior, published by MIT Press, Cambridge, MA, Stati Uniti d'America.
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Ghofraniha N., Viola I., Di Maria F., Barbarella G., Gigli G., Leuzzi L., and Conti C. (2015) “Experimental evidence of replica symmetry breaking in random lasers”, Nature communications, published by Nature Publishing Group., London, Regno Unito, vol. 6, art_n_6058 pages.
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Laurenzana A., Fibbi G., Chillà A., Margheri G., Del Rosso T., Rovida E., Del Rosso M., and Margheri F. (2015) “Lipid rafts: integrated platforms for vascular organization offering therapeutic opportunities”, Cellular and molecular life sciences (Electron. ed. ), published by Birkhäuser, Basel, Svizzera, vol. 72, pp. 1537-1557.
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Maniscalco U. and Rizzo R. (2015) “ADDING A VIRTUAL LAYER IN A SENSOR NETWORK TO IMPROVE MEASUREMENT RELIABILITY”, Series on advances in mathematics for applied sciences, published by World Scientific Publishing Co Pte Ltd., Singapore, Singapore, vol. 86, pp. 260-264.
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Marzi C. and Pirrelli V. (2015) “A Neuro-Computational Approach to Understanding the Mental Lexicon”, Journal of cognitive science (Seoul. Online), ISSN 1976-6939, published by Institute for cognitive science, Seoul national university-Seoul (Corea del Sud), vol. 16(4), pp. 493-535.
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Morlino G., Gianelli C., Borghi A. M., and Nolfi S. (2015) “Learning to manipulate and categorize in human and artificial agents”, Cognitive science, published by Elsevier Science [etc. ], Kidlington, Oxford, UK [etc. ], Stati Uniti d'America, vol. 39, pp. 39-64.
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Pagnotta S., Grifoni E., Legnaioli S., Lezzerini M., Lorenzetti G., and Palleschi V. (2015) “Comparison of brass alloys composition by laser-induced breakdown spectroscopy and self-organizing maps”, Spectrochimica acta. Part B, Atomic spectroscopy, published by Pergamon, Oxford [etc. ], Regno Unito, vol. 103-104, pp. 70-75.
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Paloscia S. and Santi E. (2015) “A comparison between two algorithms for the retrieval of soil moisture using AMSR-E data”, Frontiers in earth sciences (Internet), published by Springer, Berlin, Germania, vol. 3, pp. 1-10.
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Parodi S., Filiberti R., Marroni P., Libener R., Ivaldi G., Mussap M., Ferrari E., Manneschi C., Montani E., and Muselli M. (2015) “Differential diagnosis of pleural mesothelioma using Logic Learning Machine”, BMC bioinformatics, published by BioMed Central, [London], Regno Unito.
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Pasini A. (2015) “Artificial neural networks for small dataset analysis”, Journal of thoracic disease (Print), published by Pioneer Bioscience Publishing Company, Hong Kong, Hong Kong, vol. 7, pp. 953-960.
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Pasini A. and Mazzocchi F. (2015) “A multi-approach strategy in climate attribution studies: is it possible to apply a robustness framework?”, Environmental science & policy, published by Elsevier Science, Exeter, Regno Unito, vol. 50, pp. 191-199.
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Petrosino G. and Parisi D. (2015) “A single computational model for many learning phenomena”, Cognitive systems research, published by ScienceDirect, New York, Paesi Bassi.
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Piscioneri A., Morelli S., Mele M., Canonaco M., Bilotta E., Pantano P., Drioli E., and De Bartolo L. (2015) “Neuroprotective effect of human mesenchymal stem cells in a compartmentalized neuronal membrane system”, Acta biomaterialia, published by Elsevier, Oxford, Regno Unito, vol. 24, pp. 297-308.
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Ragosta M., D'Emilio M., and Giorgio G. A. (2015) “Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network”, Environmental monitoring and assessment (Print), published by Kluwer Academic Publishers, London, Paesi Bassi, vol. 187, art. n. 307 pages.
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Sanò P., Panegrossi G., Casella D., Di Paola F., Milani L., Mugnai A., Petracca M., and Dietrich S. (2015) “The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for AMSU/MHS observations: description and application to European case studies”, Atmospheric measurement techniques (Internet), published by Copernicus Publications, Göttingen, Germania, vol. 8, pp. 837-857.
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Santi E., Paloscia S., Pettinato S., Chirici G., Mura M., and Maselli F. (2015) “Application of neural networks for the retrieval of forest woody volume from SAR multifrequency data at l and C bands”, European Journal of Remote Sensing, published by Italian Society for Remote Sensing, Firenze, Italia, vol. 48, pp. 673-687.
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Santi, E., Paloscia S., Pettinato S., and Fontanelli G. (2015) “Application of artificial neural networks for the soil moisture retrieval from active and passive microwave spaceborne sensors”, International journal of applied earth observation and geoinformation (Online), published by Elsevier Science, [Amsterdam], Paesi Bassi.
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Seepanomwan K., Caligiore D., Cangelosi A., and Baldassarre G. (2015) “Generalization, decision making, and embodiment effects in mental rotation: a neurorobotic architecture tested with a humanoid robot”, Neural networks, published by Pergamon, New York, Stati Uniti d'America, vol. 72, pp. 31-47.
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Simione L. and Nolfi S. (2015) “Selection-for-action emerges in neural networks trained to learn spatial associations between stimuli and actions”, Cognitive processing (Print), published by Springer, Berlin, Germania, vol. 16, pp. 393-397.
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Torcini A., Luccioli S., Bonifazi P., Ben Jacob E., and Barzilai A. (2015) “Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks”, Bulletin of the American Physical Society, vol. 60, Abstract: G50. 00004 pages.
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Torcini D. A. A. (2015) “Stochastic Mean Formulation of the Dynamics of Diluted Neural Networks”, Physical review. E, Statistical, nonlinear and soft matter physics (Online), published by Published by the American Physical Society through the American Institute of Physics, Melville, N. Y., Stati Uniti d'America, vol. 91, pp. 022928-022928.
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Accetta A., Cirrincione M., Pucci M., and Vitale G. (2014) “Neural sensorless control of linear induction motors by a full-order luenberger observer considering the end effects”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. 50, pp. 1891-1904.
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Alonge F., Cirrincione M., D'Ippolito F., Pucci M., Sferlazza A., and Vitale G. (2014) “Descriptor-type kalman filter and TLS EXIN speed estimate for sensorless control of a linear induction motor”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. 50, pp. 3754-3766.
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Borgia S., Pellegrinelli S., Bianchi G., and Leonesio M. (2014) “A reduced model for energy consumption analysis in milling”, Procedia CIRP, vol. 17, pp. 529-534.
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Burioni R., Casartelli M., Di Volo M., Livi R., and Vezzani A. (2014) “Average synaptic activity and neural networks topology: A global inverse problem”, Scientific reports (Nature Publishing Group), published by Nature Publishing Group, London, Regno Unito, vol. 4, art_n_4336 pages.
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Caligiore D., Parisi D., and Baldassarre G. (2014) “Integrating Reinforcement Learning, Equilibrium Points, and Minimum Variance to Understand the Development of Reaching: A Computational Model”, Psychological review, published by American Psychological Association [etc. ], [Washington, etc. ], Stati Uniti d'America, vol. 121, pp. 389-421.
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Caligiore D., Tommasino P., Sperati V., and Baldassarre G. (2014) “Modular and hierarchical brain organization to understand assimilation, accommodation and their relation to autism in reaching tasks: a developmental robotics hypothesis”, Adaptive behavior, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 22, pp. 304-329.
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Ciszak M. and Meucci R. (2014) “Spontaneous Transitions in Deterministic Networks”, Acta Physica Polonica. B, published by Jagellonian University, Cracow, Polonia, vol. 45, pp. 1157-1165.
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Coltelli P., Barsanti L., Evangelista V., Frassanito A., and Gualtieri P. (2014) “Water monitoring: automated and real time identification and classification of algae using digital microscopy”, Environmental science-processes and impacts, vol. 16, pp. 2656-2665.
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Consoli S., Recupero D. R., and Zavarella V. (2014) “A survey on tidal analysis and forecasting methods for Tsunami detection”, Science of Tsunami Hazards, published by Dr. George Pararas-Carayannis, Stati Uniti, Stati Uniti d'America, vol. 33, pp. 1-56.
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D'Elia C., Ruscino S., Abbate M., Aiazzi B., Baronti S., and Alparone L. (2014) “SAR image classification through information-theoretic textural features, MRF segmentation, and object-oriented learning vector quantization”, IEEE journal of selected topics in applied earth observations and remote sensing (Online), published by Institute of Electrical and Electronics Engineers, Inc., New York, N. Y., Stati Uniti d'America, vol. 7, pp. 1116-1126.
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Di Piazza A., Di Piazza M. C., and Vitale G. (2014) “Estimation and Forecast of Wind Generators Production Capability for Energy Management Purpose in Smart Grids”, Renewable energy & power quality journal, published by [s. n. ], [S. l. ], Spagna, vol. 12.
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Di Volo M., Burioni R., Casartelli M., Livi R., and Vezzani A. (2014) “Heterogeneous mean field for neural networks with short-term plasticity”, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, published by Published by the American Physical Society through the American Institute of Physics, New York, N. Y., Stati Uniti d'America, vol. 90, pp. 2811-2811.
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Ferone A. and Maddalena L. (2014) “Neural Background Subtraction for Pan-Tilt-Zoom Cameras”, IEEE transactions on systems, man, and cybernetics, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 44, pp. 571-579.
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Ferrarin C., Zaggia L., Paschini E., Scirocco T., Lorenzetti G., Bajo M., Penna P., Francavilla M., D'Adamo R., and Guerzoni S. (2014) “Hydrological regime and renewal capacity of the micro-tidal Lesina Lagoon, Italy”, Estuaries and coasts (Online), published by Estuarine Research Federation, Port Republic, Md., Stati Uniti d'America, pp. 79-93.
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Gaudio P., Murari A., Gelfusa M., Lupelli I., and Vega J. (2014) “An alternative approach to the determination of scaling law expressions for the L-H transition in Tokamaks utilizing classification tools instead of regression”, Plasma physics and controlled fusion (Print), published by Institute of Physics, Bristol, Regno Unito, vol. 56.
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Losi G., Mariotti L., and Carmignoto G. (2014) “GABAergic interneuron to astrocyte signalling: a neglected form of cell communication in the brain”, Philosophical transactions-Royal Society. Biological sciences (Print), published by Royal Society, London, Regno Unito, vol. 369.
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Luccioli S., Ben Jacob E., Barzilai A., Bonifazi P., and Torcini A. (2014) “Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks”, PLOS computational biology (Online), published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 10, e1003823 pages.
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Maddalena L. and Petrosino A. (2014) “The 3dSOBS+ algorithm for moving object detection”, Computer vision and image understanding (Print), published by Academic Press, San Diego, Stati Uniti d'America, vol. 122, pp. 65-73.
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Maddalena L., Petrosino A., and Russo F. (2014) “People counting by learning their appearance in a multi-view camera environment”, Pattern recognition letters, published by North-Holland, Amsterdam, Paesi Bassi, vol. 36, pp. 125-134.
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Mikkelsen K., Imparato A., and Torcini A. (2014) “Sisyphus effect in pulse-coupled excitatory neural networks with spike-timing-dependent plasticity”, Physical review. E, Statistical, nonlinear and soft matter physics (Online), published by Published by the American Physical Society through the American Institute of Physics, Melville, N. Y., Stati Uniti d'America, vol. 89, 062701 pages.
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Mladenova I. E., Jackson T. J., Njoku E., Bindlish R., Chan S., Cosh M. H., Holmes T. R. H., De Jeu R. A. M., Jones L., Kimball J., Paloscia S., and Santi E. (2014) “Remote monitoring of soil moisture using passive microwave-based techniques-Theoretical basis and overview of selected algorithms for AMSR-E”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 144, pp. 197-213.
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Mongelli M. and Scanzio S. (2014) “Approximating Optimal Estimation of Time Offset Synchronization With Temperature Variations”, IEEE transactions on instrumentation and measurement, published by Institute of Electrical and Electronics Engineers., New York, Stati Uniti d'America, vol. 63, pp. 2872-2881.
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Ninaus M. and Kober S. E. (2014) “Neurophysiological methods for monitoring brain activity in serious games and virtual environments: A review”, International journal of technology enhanced learning (Print), published by Inderscience, Olney, Regno Unito, vol. 6, pp. 78-103.
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Olmi S., Torcini A., and Politi A. (2014) “Linear stability in networks of pulse-coupled neurons”, Frontiers in computational neuroscience, published by Frontiers Research Foundation, Lausanne, Svizzera, vol. 8, art_n_8 pages.
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Papo D., Zanin M., Pineda Pardo J. A., Boccaletti S., and Buldú J. M. (2014) “Functional brain networks: great expectations, hard times and the big leap forward”, Philosophical transactions-Royal Society. Biological sciences (Print), published by Royal Society, London, Regno Unito, vol. 369, 20130525 pages.
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Russo T., Parisi A., Garofalo G., Gristina M., Cataudella S., and Fiorentino F. (2014) “SMART: A Spatially Explicit Bio-Economic Model for Assessing and Managing Demersal Fisheries, with an Application to Italian Trawlers in the Strait of Sicily”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 9.
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Salerno E., Tonazzini A., Grifoni E., Lorenzetti G., Legnaioli S., Lezzerini M., Marras L., and Pagnotta S P. V. (2014) “Analysis of multispectral images in cultural heritage and archaeology”, Journal of applied spectroscopy, published by Consultants Bureau [etc. ], New York, Stati Uniti d'America, vol. 1, pp. 22-27.
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Sanò P., G P., D C., F D. P., L M., A M., M P., and S D. (2014) “The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for AMSU/MHS observations: description and application to European case studies”, Atmospheric measurement techniques. Papers in open discussion, published by Copernicus Publications, Göttingen, Germania, vol. 7, pp. 9411-9411.
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Santi E., Pettinato S., Paloscia S., Pampaloni P., Fontanelli G., Crepaz A., and Valt M. (2014) “Monitoring of Alpine snow using satellite radiometers and artificial neural networks”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 144, pp. 179-186.
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Accetta A., Cirrincione M., Pucci M., and Gianpaolo V. (2013) “MRAS Speed Observer for High-Performance Linear Induction Motor Drives Based on Linear Neural Networks”, IEEE transactions on power electronics, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 28, pp. 123-134.
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Alessandri A., Cervellera C., and Gaggero M. (2013) “Predictive control of container flows in maritime intermodal terminals”, IEEE transactions on control systems technology (Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 21, pp. 1423-1431.
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Augello A., Infantino I., Pilato G., Rizzo R., and Vella F. (2013) “Binding representational spaces of colors and emotions for creativity”, Biologically inspired cognitive architectures (Print), published by Elsevier, Amsterdam, Paesi Bassi, vol. 5, pp. 64-71.
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Bizon K., Continillo G., Mancaruso E., and Vaglieco B. M. (2013) “Towards on-line prediction of the in-cylinder pressure in diesel engines from engine vibration using artificial neural networks”, SAE technical paper series, published by Society of Automotive Engineers, Warrendale, Penn., Stati Uniti d'America.
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Caligiore D. and Fischer M. H. (2013) “Vision, action and language unified through embodiment”, Psychological research (Internet), published by Springer., Heidelberg, Germania, vol. 77, pp. 1-6.
274
Campi G., Pezzotti G., Fratini M., Ricci A., Burghammer M., Cancedda R., Mastrogiacomo M., Bukreeva I., and Cedola A. (2013) “Imaging regenerating bone tissue based on neural networks applied to high resolution micro-diffraction measurements”, Applied physics letters, published by American Institute of Physics., New York [etc. ], Stati Uniti d'America, vol. 103, 253703 pages.
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Chersi F., Donnarumma F., and Pezzulo G. (2013) “Mental imagery in the navigation domain: A computational model of sensory-motor simulation mechanisms”, Adaptive behavior, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 21, pp. 251-262.
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Chiarello F., Carelli P., Castellano M. G., and Torrioli G. (2013) “Artificial neural network based on SQUIDs: demonstration of network training and operation”, Superconductor science & technology (Online), published by IOP Publishing., [Bristol], Regno Unito, vol. 26, pp. 125009-1-125009-6.
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Ciancio A. L., Zollo L., Baldassarre G., Caligiore D., and Guglielmelli E. (2013) “The role of learning and kinematic features in dexterous manipulation: A comparative study with two robotic hands”, International journal of advanced robotic systems (Print), published by Institute for Production Engineering. Intelligent Manufacturing Systems. Vienna University of Technology., Wien, Austria, vol. 10.
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Cirrincione M., Pucci M., and Vitale G. (2013) “Neural MPPT of Variable Pitch Wind Generators with Induction Machines in a Wide Wind Speed Range”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. 49, pp. 942-953.
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Coppini G., Miniati M., Monti S., Paterni M., Favilla R., and Ferdeghini E. (2013) “A computer-aided diagnosis approach for emphysema recognition in chest radiography”, Medical engineering & physics, ISSN 1350-4533, published by Butterworth-Heinemann, Oxford (Regno Unito), vol. 35, pp. 63-73.
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Coro G., Pagano P., and Ellenbroek A. (2013) “Combining simulated expert knowledge with Neural Networks to produce Ecological Niche Models for Latimeria chalumnae”, Ecological modelling, published by Elsevier, Shannon;, Paesi Bassi, vol. 268, pp. 55-63.
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Di Garbo A., Barbi M., and Chillemi S. (2013) “The role of glutamatercic and GABAergic synapses on the dynamics of neural networks: How they impact the transition to seizure?”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 114, pp. 15-23.
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Di Noia A., Sellitto P., Del Frate F., Cervino M., Iarlori M., and Rizi V. (2013) “Tropospheric ozone column retrieval from OMI data by means of neural networks: a validation exercise with ozone soundings over Europe”, EURASIP Journal on Advances in Signal Processing (Online), published by Hindawi Publishing Corporation, Cairo, Egitto.
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Di Piazza M. C., Pucci M., and Vitale G. (2013) “Intelligent Power Conversion System Management for Photovoltaic Generation”, Sustainable Energy Technologies and Assessments, published by Elsevier, vol. 2, pp. 19-30.
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Di Volo M. and Livi R. (2013) “The influence of noise on synchronous dynamics in a diluted neural network”, Chaos, solitons and fractals, published by Pergamon., Oxford, Regno Unito, vol. 57, pp. 54-61.
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Ferone A., Maddalena L., and Petrosino A. (2013) “Neural Moving Object Detection by Pan-Tilt-Zoom Cameras”, Smart innovation, systems and technologies (Print), published by Heidelberg, Heidelberg;, Germania, vol. 19, pp. 129-138.
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Ferrauto T., Parisi D., Di Stefano G., and Baldassarre G. (2013) “Different Genetic Algorithms and the Evolution of Specialization: A Study with Groups of Simulated Neural Robots”, Artificial life, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 19, pp. 221-253.
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Heintze E., El Hallak F., Clauß C., Rettori A., Pini M. G., Totti F., Dressel M., and Bogani L. (2013) “Dynamic control of magnetic nanowires by light-induced domain-wall kickoffs”, Nature materials (Print), published by Nature Publishing Group., London, Regno Unito, vol. 12, pp. 202-206.
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Ielpo P., Cassano D., Uricchio V. F., Lopez A., Pappagallo G., Trizio L., and De Gennaro G. (2013) “IDENTIFICATION OF POLLUTION SOURCES AND CLASSIFICATION OF APULIA REGION GROUNDWATERS BY MULTIVARIATE STATISTICAL METHODS AND NEURAL NETWORKS”, Transactions of the ASABE (Print), published by American Society of Agricultural and Biological Engineers, St. Joseph, MI, Stati Uniti d'America, vol. 56, pp. 1377-1386.
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Infantino I., Pilato G., Rizzo R., and Vella F. (2013) “Humanoid Introspection: A Practical Approach”, International journal of advanced robotic systems (Print), published by Institute for Production Engineering. Intelligent Manufacturing Systems. Vienna University of Technology., Wien, Austria, vol. 10.
290
Leone A. P., Leone N., and Rampone S. (2013) “An Application of vis-NIR reflectance spectroscopy and Artifi-cial Neural Networks to the Prediction of soil Organic Carbon content in Southern Italy”, Fresenius environmental bulletin, published by Parlar Scientific Publications, Freising, Germania, vol. 22.
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Leone A. P., Leone N., and Rampone S. (2013) “An application of vis-NIR reflectance spectroscopy and Artificial Neural Networks to the prediction of soil organic carbon content in southern Italy”, Fresenius environmental bulletin, published by Parlar Scientific Publications, Freising, Germania, vol. 22, pp. 1230-1238.
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Livi R. (2013) “On brain fluctuations and the challenges ahead”, Chaos, solitons and fractals, published by Pergamon., Oxford, Regno Unito, vol. 55, pp. 60-63.
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Maddalena L. and Petrosino A. (2013) “Stopped Object Detection by Learning Foreground Model in Videos”, IEEE Transactions on Neural Networks and Learning Systems, published by Institute of Electrical and Electronics Engineers,-New York, NY, USA, Stati Uniti d'America, vol. 24, pp. 723-735.
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Mikkelsen K., Imparato A., and Torcini A. (2013) “Emergence of slow collective oscillations in neural networks with spike-timing dependent plasticity”, Physical review letters (Print), published by American Physical Society., [Woodbury, N. Y., etc. ], Stati Uniti d'America, vol. 110, art_n_208101 pages.
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Morbelli S. D., Perneczky R., Drzezga A. E., Frisoni G. B., Caroli A., Van Berckel B. N. M., Ossenkoppele R., Guedj ÉR., Didic M., Brugnolo A., Naseri M., Sambuceti G., Pagani M., and Nobili F. M. (2013) “Metabolic networks underlying cognitive reserve in prodromal Alzheimer disease: A European Alzheimer Disease Consortium Project”, The Journal of nuclear medicine (1978), published by Society of Nuclear Medicine., [New York], Stati Uniti d'America, vol. 54, pp. 894-902.
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Mordenti M., Ferrari E., Pedrini E., Fabbri N., Campanacci L., Muselli M., and Sangiorgi L. (2013) “Validation of a new multiple osteochondromas classification through Switching Neural Networks”, American journal of medical genetics. Part A, published by Wiley-Liss, Hoboken, N. J., Stati Uniti d'America, vol. 161A, pp. 556-560.
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Mugnai A., Smith E. A., Tripoli G. J., Bizzarri B., Casella D., Dietrich S., Di Paola F., Panegrossi G., and Sanò P. (2013) “CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations”, Natural hazards and earth system sciences (Online), published by Copernicus Publ., Göttingen, Germania, vol. 13, pp. 887-912.
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Murari A., Arena P., Buscarino A., Fortuna L., Iachello M., and Contributors J. (2013) “On the identification of instabilities with neural networks on JET”, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, vol. 720, pp. 2-6.
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Napoli G., Ferraro M., Sergi F., Brunaccini G., and Antonucci V. (2013) “Data driven models for a PEM fuel cell stack performance prediction”, International journal of hydrogen energy, published by Pergamon Press., New York, Regno Unito, vol. 38, pp. 11628-11638.
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Olmi, Simona, Torcini, and Alessandro (2013) “Coherent activity in excitatory pulse-coupled networks”, Scholarpedia journal, published by Scholarpedia. org, San Diego, CA, Stati Uniti d'America, vol. 8, 30928 pages.
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Paloscia S., Pettinato S., Santi E., Notarnicola C., Pasolli L., and Reppucci A. (2013) “Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 134, pp. 234-248.
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Pasini A. and Modugno G. (2013) “Climatic attribution at the regional scale: a case study on the role of circulation patterns and external forcings”, Atmospheric science letters, published by Academic Press, London, UK, Regno Unito, vol. 14, pp. 301-305.
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Penzes P., Buonanno A., Passafaro M., Sala C., and Sweet R. A. (2013) “Developmental vulnerability of synapses and circuits associated with neuropsychiatric disorders”, Journal of neurochemistry, published by Blackwell, Oxford, Regno Unito.
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Pierini, J. O., Lovallo, M., Telesca, L., Gómez, and E. A. D. (2013) “Investigating prediction performance of an artificial neural network and a numerical model of the tidal signal at Puerto Belgrano, Bahia Blanca Estuary (Argentina)”, Acta Geophysica (Druk), published by Springer-Verlag, Berlin, Polonia, vol. 61, pp. 1522-1537.
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Pifferi M., Bush A., Montemurro F., Pioggia G., Piras M., Tartarisco G., Cicco M., Chinellato I., Cangiotti A., and Boner A. L. (2013) “Rapid diagnosis of primary ciliary dyskinesia: cell culture and soft computing analysis”, The European respiratory journal, ISSN 0903-1936, published by European Respiratory Society Journals Ltd., Lausanne, vol. 41(4), pp. 960-965.
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Rizzo R. (2013) “A new training method for large self organizing maps”, Neural Processing Letters, published by D facto s. a., Bruxelles, Belgio, vol. 37, pp. 263-275.
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Santi E., Paloscia S., Pettinato S., Notarnicola C., Pasolli L., and Pistocchi A. (2013) “Comparison between SAR Soil Moisture Estimates and Hydrological Model Simulations over the Scrivia Test Site”, Remote sensing (Basel), published by Molecular Diversity Preservation International, Basel, vol. 5, pp. 4961-4976.
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Taglialatela F., Lavorgna M., Mancaruso E., and Vaglieco B. M. (2013) “Determination of combustion parameters using engine crankshaft speed”, Mechanical systems and signal processing, published by Academic Press, Orlando, Regno Unito, vol. 38, pp. 628-633.
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Ware, Abc R., Cimini, De D., Campos, E., Giuliani, G. G., Albers, Hi S., Nelson, M., Koch, S. E. J., Joe, P. K., Cober, and S. K. (2013) “Thermodynamic and liquid profiling during the 2010 Winter Olympics”, Atmospheric research (Print), published by Elsevier, Tokyo;, Paesi Bassi, vol. 132, pp. 278-290.
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Zippo A. G., Gelsomino G., Van Duin P., Nencini S., Caramenti G. C., Valente M., and Biella G. E. M. (2013) “Small-world networks in neuronal populations: A computational perspective”, Neural networks, published by Pergamon, New York, Stati Uniti d'America, vol. 44, pp. 143-156.
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Accetta A., Cirrincione M., and Pucci M. (2012) “TLS EXIN based neural sensorless control of a high dynamic PMSM”, Control engineering practice, published by Pergamon Press., Oxford, Regno Unito, vol. 20, pp. 725-732.
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Accetta A., Cirrincione M., Pucci M., and Vitale G. (2012) “Sensorless Control of PMSM Fractional Horsepower Drives by Signal Injection and Neural Adaptive-Band Filtering”, IEEE transactions on industrial electronics (1982. Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 59, pp. 1355-1366.
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Benfenati V., Stahl K., Gomis Perez C., Toffanin S., Sagnella A., Torp R., Kaplan D. L., Ruani G., Omenetto F. G., Zamboni R., and Muccini M. (2012) “Biofunctional Silk/Neuron Interfaces”, Advanced functional materials (Print), published by Wiley-VCH, Weinheim, Germania, vol. 22, pp. 1871-1884.
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Boattini A., Lisa A., Fiorani O., Zei G., Pettener D., and Manni F. (2012) “General Method to Unravel Ancient Population Structures through Surnames, Final Validation on Italian Data”, Human biology (Print), published by Wayne State University Press [etc. ], [Detroit, Mich., etc. ], Stati Uniti d'America, vol. 84, pp. 235-270.
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Cecchinato L., Corradi M., Cosi G., Minetto S., and Rampazzo M. (2012) “A real-time algorithm for the determination of R744 systems optimal high pressure”, International journal of refrigeration, published by IPC Science and Technology Press, Guildford, Surrey, Regno Unito, vol. 35.
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Cerasa A., Bilotta E., Augimeri A., Cherubini A., Pantano P., Zito G., Lanza P. L., Valentino P., Gioia M. C., and Quattrone A. (2012) “A Cellular Neural Network methodology for the automated segmentation of multiple sclerosis lesions”, Journal of neuroscience methods, published by Elsevier, Shannon;, Paesi Bassi, vol. 203, pp. 193-199.
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Chersi F. and Pezzulo G. (2012) “Using hippocampal-striatal loops for spatial navigation and goal-directed decision-making”, Cognitive processing (Print), ISSN 1612-4782, published by Springer-Berlin (Germania), vol. 13(1), pp. 125-129.
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Cirrincione M., Pucci M., and Vitale G. (2012) “Growing Neural Gas-Based MPPT of Variable Pitch”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. 48, pp. 1006-1016.
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Ciszak M., Euzzor S., Farini A., Arecchi F. T., and Meucci R. (2012) “Modeling bistable perception with a network of chaotic neurons”, Cybernetics and physics (Online), published by Laboratory "Control of Complex Systems", IPME RAS, St. Petersburg, Russia, vol. 1, pp. 165-168.
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Davoli F., Marchese M., and Mongelli M. (2012) “Non-linear coding decoding strategies exploiting spatial correlation in wireless sensor networks”, IET communications (Print), published by Institution of Engineering and Technology, Stevenage, Regno Unito, vol. 6, pp. 2198-2207.
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Dipoppa M., Krupa M., Alessandro T., and G. B. S. (2012) “Splay States in Finite Pulse-Coupled Networks of Excitable Neurons”, SIAM journal on applied dynamical systems, published by Society of Industrial and Applied Mathematics, Philadelphia, PA, Stati Uniti d'America, vol. 11, pp. 864-894.
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Donnarumma F., Prevete R., and Trautteur G. (2012) “Programming in the brain: a neural network theoretical framework”, Connection science (Print), published by Carfax Publishing, Abingdon (P. O. Box 25, Abingdon, Oxfordshire OX14 3UE), Regno Unito, vol. 24, pp. 71-90.
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Falavigna G. (2012) “Financial ratings with scarce information: A neural network approach”, Expert systems with applications, published by Pergamon, Oxford, Regno Unito, vol. 39, pp. 1784-1792.
324
Gaggioli A., Pioggia G., Tartarisco G., Baldus G., Ferro M., Cipresso P., Serino S., Popleteev A., Gabrielli S., Maimone R., and Riva G. (2012) “A system for automatic detection of momentary stress in naturalistic settings”, Studies in health technology and informatics (Print), published by IOS Press, Tokyo;, Paesi Bassi, vol. 181, pp. 182-186.
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Madricardo F., Tegowski J., and Donnici S. (2012) “Automated detection of sedimentary features using wavelet analysis and neural networks on single beam echosounder data: A case study from the Venice Lagoon, Italy”, Continental shelf research, published by Pergamon Press., Oxford;, Regno Unito, vol. 43, pp. 43-54.
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Morlino G., Gianelli C., Borghi A. M., and Nolfi S. (2012) “Category learning through action: A study with human and artificial agents”, Cognitive processing (Print), published by Springer, Berlin, Germania, vol. 13, pp. s47-s48.
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Murari A., Mazon D., Martin N., Vagliasindi G., Gelfusa M., and Contributors J. (2012) “Exploratory Data Analysis Techniques to Determine the Dimensionality of Complex Nonlinear Phenomena: The L-to-H Transition at JET as a Case Study”, IEEE transactions on plasma science, published by Institute of Electrical and Electronics Engineers., New York, Stati Uniti d'America, vol. 40, pp. 1386-1394.
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Olmi S., Politi A., and Torcini A. (2012) “Stability of the splay state in networks of pulse-coupled neurons”, The Journal of Mathematical Neuroscience, published by Springer Open, Berlin (Germania), Germania, vol. 2.
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Parisi D. (2012) “STUDYING THE IMPACT OF LANGUAGE ON THE MIND BY CONSTRUCTING ROBOTS THAT HAVE LANGUAGE”, Advances in Complex Systems, published by World Scientific Publishing, Singapore, Singapore, vol. 15.
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Pasini, A., Langone, and R. (2012) “Influence of circulation patterns on temperature behavior at the regional scale: A case study investigated via neural network modeling”, Journal of Climate, vol. 25, pp. 2123-2128.
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Pierini J., Gomez E., and Telesca L. (2012) “Prediction of water flows in Colorado River, Argentina”, Latin american journal of aquatic research, published by Escuela de Ciencias del Mar, Pontificia Universidad Católica de Valparaíso, Valparaíso, Cile, vol. 40, pp. 872-880.
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Roman, M., Jitaru, P., Agostini, M., Cozzi, G., Pucciarelli, S., Nitti, D., Bedin, C., Barbante, C., and G. (2012) “Serum seleno-proteins status for colorectal cancer screening explored by data mining techniques-a multidisciplinary pilot study”, Microchemical journal (Print), published by Academic Press [etc. ], New York, Stati Uniti d'America, vol. 105, pp. 124-132.
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Santi E., Pettinato S., Paloscia S., Pampaloni P., Macelloni G., and Brogioni M. (2012) “An algorithm for generating soil moisture and snow depth maps from microwave spaceborne radiometers: HydroAlgo”, Hydrology and earth system sciences, published by Copernicus Publ., Göttingen, Germania, vol. 16, pp. 3659-3676.
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Sozio P., Rapino M., Di Valerio V., Laserra S., Pacella S., Di Stefano A., and Cataldi A. (2012) “pPKCalpha-mediated effect on in vitro A-beta production in response to gamma secretase inhibitor LY411575 in rat CTXTNA2 astrocytes”, Journal of Biological Regulators & Homeostatic Agents (Testo stamp. ), published by Wichtig editore, Milano, Italia, vol. 26, pp. 245-251.
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Tartarisco G., Baldus G., Corda D., Raso R., Arnao A., Ferro M., Gaggioli A., and Pioggia G. (2012) “Personal Health System architecture for stress monitoring and support to clinical decisions”, Computer communications, ISSN 0140-3664, published by IPC Science and Technology Press, Guildford (Regno Unito), vol. 35(11), pp. 1296-1305.
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Tattini L., Olmi S., and Torcini A. (2012) “Coherent periodic activity in excitatory Erdös-Renyi neural networks: The role of network connectivity”, Chaos (Clayton), published by Union Council, Monash University, Clayton, Vic., Australia, vol. 22, 023133 pages.
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Alessandri A., Baglietto M., Battistelli G., and Gaggero M. (2011) “Moving-horizon state estimation for nonlinear systems using neural networks”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 22, pp. 768-780.
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Bizon K., Continillo G., Mancaruso E., and Vaglieco B. M. (2011) “Reconstruction of in-cylinder pressure in a Diesel engine from vibration signal using a RBF neural network model”.
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Borghi A. M., Di Ferdinando A., and Parisi D. (2011) “Objects, spatial compatibility, and affordances: A connectionist study”, Cognitive systems research, published by ScienceDirect, New York, Paesi Bassi, vol. 12, pp. 33-34.
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Cervellera C. and Macciò D. (2011) “A comparison of global and semi-local approximation in T-stage stochastic optimization”, European journal of operational research, published by Elsevier, Amsterdam, Paesi Bassi, vol. 208, pp. 109-118.
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Chavez Ramirez A. U., Munoz Guerrero R., Sanchez Huerta V., Ramirez Arredondo J. M., Ornelas R., Arriaga L. G., Siracusano S., Brunaccini G., Napoli G., Antonucci V., and Aricò A. S. (2011) “Dynamic model a PEM electrolyzer based on artificial neural networks”, Journal of new materials for electrochemical systems, published by s. n., Montréal, Canada, vol. 14, pp. 113-119.
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Delogu R. S. and Terranova D. (2011) “EM signal integrity via neural network analysis for the RFX-mod experiment”, Fusion engineering and design, published by North Holland., Amsterdam, Paesi Bassi, vol. 86, pp. 1095-1098.
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Dottorini T., Sole G., Nunziangeli L., Baldracchini F., Senin N., Mazzoleni G., Proietti C., Balaci L., and Crisanti A. (2011) “Serum IgE Reactivity Profiling in an Asthma Affected Cohort”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 6.
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Falavigna G. (2011) “An artificial neural network approach for assigning rating judgements to Italian Small Firms”, Working paper (CERIS-CNR, Online), published by CERIS, Istituto di ricerca sull'impresa e lo sviluppo, Moncalieri, TO, Italia.
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Lei X., Ostwald D., Hu J., Qiu C., Porcaro C., Bagshaw A. P., and Yao D. (2011) “Multimodal functional network connectivity: An EEG-fMRI fusion in network space”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 6.
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Lim C. W., Chan S. H., and Visconti A. (2011) “Feed-forward neural network assisted by discriminant analysis for the spectroscopic discriminantion of cracked spores Ganoderma lucidum: A prospective biotechnology production tool”, vol. 1, pp. 40-40.
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Madi A., Kenett D. Y., Bransburg Zabary S., Merbl Y., Quintana F. J., Boccaletti S., Tauber A. I., Cohen I. R., and Ben Jacob E. (2011) “Analyses of antigen dependency networks unveil immune system reorganization between birth and adulthood”, Chaos (Woodbury N. Y. ), published by American Institute of Physics, Woodbury, NY, Stati Uniti d'America, vol. 211, 016109 pages.
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Mezzanotte V., Bresciani M., Canobbio S., Giardino C., Antonelli M., Bortoluzzi A., Foltran F., Panizza A., Pietrosanti A., Ren Y., De Biase L. M., and Nurizzo C. (2011) “Monitoring, environmental emergencies management and water treatment improvement of freshwater lakes in China: The Chao Lake case study”, Water science and technology: water supply (Print), published by IWA Publishing, London, vol. 11, pp. 490-496.
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Parisi D. (2011) “The other half of the embodied mind”, Frontiers in Psychology, published by Frontiers media, Lausanne, Svizzera, vol. 2, pp. 1-8.
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Pilato G., Maniscalco U., and Vassallo G. (2011) “Soft Sensor based on E-alphaNETs”, Frontiers in artificial intelligence and applications (Print), published by Springfield, Amsterdam, Paesi Bassi, vol. 226, pp. 172-179.
351
Scarpetta S., Giacco F., and De Candia A. (2011) “Storage capacity of phase-coded patterns in sparse neural networks”, Europhysics letters (Print), published by EDP sciences, Les Ulis, Francia, vol. 95, pp. 5075-5079.
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Stern F., Agdrup K., Kim S. Y., Hochbaum A. C., Rhee K. P., Quadvlieg F., Perdon P., Hino T., Broglia R., and Gorski J. (2011) “Experience from SIMMAN 2008-The First Workshop on Verification and Validation of Ship Maneuvering Simulation Methods”, Journal of ship research (Print), published by Society of Naval Architects and Marine Engineers., New York, Stati Uniti d'America, vol. 55, pp. 135-147.
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Tuci E., Ferrauto T., Zeschel A., Massera G., and Nolfi S. (2011) “An Experiment on Behavior Generalization and the Emergence of Linguistic Compositionality in Evolving Robots”, IEEE transactions on autonomous mental development (Print), published by IEEE, Piscataway, NJ, Stati Uniti d'America, vol. 3, pp. 176-189.
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Urso A., Rizzo R., Gaglio S., Di Fatta G., and Fiannaca A. (2011) “Simulated Annealing Technique for Fast Learning of SOM Networks”, Neural computing & applications (Print), published by Springer., Godalming, Regno Unito, vol. 22, pp. 889-899.
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Verpelli C., Dvoretskova E., Vicidomini C., Rossi F., Chiappalone M., Schoen M., Di Stefano B., Mantegazza R., Broccoli V., Bockers T., Dityatev A., and Sala C. (2011) “Importance of Shank3 protein in regulating metabotropic glutamate receptor 5 (mGluR5) expression and signaling at synapses”, The Journal of biological chemistry (Print), published by American Society for Biochemistry and Molecular Biology [etc. ], [Baltimore, etc. ], Stati Uniti d'America, vol. 286, pp. 34839-34850.
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Zemella G., De March D., Borrotti M., and Poli I. (2011) “Optimised design of energy efficient building façades via Evolutionary Neural Networks”, Energy and buildings, published by Elsevier, Lausanne;, Paesi Bassi, vol. 43, pp. 3297-3302.
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Bajo M. and Umgiesser G. (2010) “Storm surge forecast through a combination of dynamic and neural network models”, Ocean modelling (Oxf., Print), published by Elsevier., Oxford, Regno Unito, vol. 33, pp. 1-9.
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Caligiore D., Borghi A., Parisi D., and Baldassarre G. (2010) “TRoPICALS: A Computational Embodied Neuroscience Model of Compatibility Effects”, Psychological review, published by American Psychological Association [etc. ], [Washington, etc. ], Stati Uniti d'America, vol. 117, pp. 1188-1228.
View DOI resources359
Caviglione L. (2010) “A Simple Neural Framework for Bandwidth Reservation of VoIP Communications in Cost-Effective Devices”, IEEE transactions on consumer electronics, published by Institute of Electrical and Electronics Engineers, New York, Stati Uniti d'America, vol. 56, pp. 1252-1257.
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Cervellera C., Macciò D., and Muselli M. (2010) “Efficient global maximum likelihood estimation through kernel methods”, Neural networks, published by Pergamon, New York, Stati Uniti d'America, vol. 23, pp. 917-925.
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Chàvez Ramirez A. U., Muñoz Guerrero R., Duròn Torres S. M., Ferraro M., Brunaccini G., Sergi F., Antonucci V., and Arriaga L. G. (2010) “High power fuel cell simulator based on artificial neural network”, International journal of hydrogen energy, published by Pergamon Press., New York, Regno Unito, vol. 35, pp. 12125-12133.
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Crespo Garcia M., Cantero J. L., Pomyalov A., Boccaletti S., and Atienza M. (2010) “Functional neural networks underlying semantic encoding of associative memories”, NeuroImage (Orlando Fla., Print), published by Academic Press, Orlando, FL, Stati Uniti d'America, vol. 50, pp. 1258-1270.
363
De Gregorio M., França F. M. G., Grieco B. P. A., and Lima P. M. V. (2010) “Producing pattern examples from "mental" images”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 73, pp. 1057-1064.
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Di Piazza M. C., Pucci M., Ragusa A., and Vitale G. (2010) “Analytical Versus Neural Real-Time Simulation of a Photovoltaic Generator Based on a DC-DC Converter”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. 6, pp. 2501-2510.
365
Ferro M., Pezzulo G., and Pirrelli V. (2010) “Morphology, Memory and the Mental Lexicon”, Lingue e linguaggio, ISSN 1720-9331, published by Il Mulino, Bologna (Italia), vol. 2, pp. 203-242.
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Giardino C., Bresciani M., Pilkaityté R., Bartoli M., and Razinkovas A. (2010) “In situ measuraments and satellite remote sensing of case2 waters: first results from the Curonian Lagoon”, Oceanology (Washington. 1965), published by MAIK "Nauka/Interperiodica" Pub., [Moscow, Russia], Russia, vol. 52(2), pp. 197-210.
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Giovannelli F., Silingardi D., Borgheresi A., Feurra M., Amati G., Pizzorusso T., Viggiano M., Zaccara G., Berardi N., and Cincotta M. (2010) “Involvement of the parietal cortex in perceptual learning (Eureka effect): an interference approach using rTMS”, Neuropsychologia (Print), published by Pergamon Press., Oxford, Regno Unito, vol. 48, pp. 1807-1812.
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Langella G., Basile A., Bonfante A., and Terribile F. (2010) “High-resolution space-time rainfall analysis using integrated ANN inference systems”, Journal of hydrology (Amst. ), published by Elsevier, Oxford;, Paesi Bassi, vol. 387, pp. 328-342.
369
Luccioli S. and Politi A. (2010) “Irregular collective behavior of heterogeneous neural networks”, Physical review letters (Print), published by American Physical Society., [Woodbury, N. Y., etc. ], Stati Uniti d'America, vol. 105, 158104 pages.
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Maddalena L. and Petrosino A. (2010) “A Fuzzy Spatial Coherence-based Approach to Background/ Foreground Separation for Moving Object Detection”, Neural computing & applications (Print), published by Springer., Godalming, Regno Unito, vol. 19-0, pp. 179-186.
View web resourcesView DOI resources371
Massera G., Tuci E., Ferrauto T., and Nolfi S. (2010) “The Facilitatory Role of Linguistic Instructions on Developing Manipulation Skills”, IEEE computational intelligence magazine, published by Institute of Electrical and Electronics Engineers, New York, Stati Uniti d'America, vol. 5, pp. 33-42.
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Miniati M., Coppini G., Monti S., Bottai M., Paterni M., and Ferdeghini E. M. (2010) “Computer-aided Recognition of Emphysema on Digital Chest Radiography”, European journal of radiology, ISSN 0720-048X, published by Georg Thieme-Stuttgart (Paesi Bassi), vol. 80(2), pp. 169-175.
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Mirolli M., Ferrauto T., and Nolfi S. (2010) “Categorisation through Evidence Accumulation in an Active Vision System”, Connection science (Print), published by Carfax Publishing, Abingdon (P. O. Box 25, Abingdon, Oxfordshire OX14 3UE), Regno Unito, vol. 22, pp. 331-354.
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Murari A., Vagliasindi G., De Fiore S., Arena E., Arena P., Fortuna L., Andrew Y., Johnson M., and Jet Efda C. (2010) “Neural computing methods to determine the relevance of memory effects in nuclear fusion”, Fusion science and technology, published by American Nuclear Society, La Grange Park, Ill., Stati Uniti d'America, vol. 58, pp. 695-705.
View web resourcesView DOI resources375
Murari A., Vega J., Mazon D., Patané D., Vagliasindi G., Arena P., Martin N., Martin N. F., Rattá G., Caloone V., and Jet Efda C. (2010) “Machine learning for the identification of scaling laws and dynamical systems directly from data in fusion”, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, vol. 623, pp. 850-854.
View DOI resources376
Odermatt D., Giardino C., and Heege T. (2010) “Chlorophyll retrieval with MERIS Case-2-Regional in perialpine lakes”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 114, pp. 607-617.
377
Ognibene D., Pezzulo G., and Baldassarre G. (2010) “Learning to Look in Different Environments: An Active-Vision Model which Learns and Readapts Visual Routines”, Lecture notes in computer science, ISSN 0302-9743, published by Springer-Berlin (Germania), vol. 6226/, pp. 199-210.
View DOI resources378
Olmi S., Livi R., Politi A., and Torcini A. (2010) “Collective oscillations in disordered neural networks”, Physical review. E, Statistical, nonlinear, and soft matter physics (Print), published by Published by the American Physical Society through the American Institute of Physics, Melville, NY, Stati Uniti d'America, vol. 81(4), 046119 pages.
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Olmi S., Politi A., and Torcini A. (2010) “Collective chaos in pulse-coupled neural networks”, Europhysics letters (Print), published by EDP sciences, Les Ulis, Francia, vol. 92(6), 60007 pages.
View DOI resources380
Paloscia S., Pampaloni P., Pettinato S., and Santi E. (2010) “Generation of soil moisture maps from ENVISAT/ASAR images in mountainous areas: a case study”, International journal of remote sensing (Print), published by Taylor & Francis Ltd., London, Regno Unito, vol. 31, pp. 2265-2276.
View DOI resources381
Pasini A. and Langone R. (2010) “Attribution of precipitation changes on a regional scale by neural network modeling: A case study”, Water (Basel), published by Molecular Diversity Preservation International, Basel, vol. 2, pp. 321-332.
View DOI resources382
Pasini A., Langone R., Maimone F., and Pelino V. (2010) “Energy-based predictions in Lorenz system by a unified formalism and neural network modelling”, Nonlinear processes in geophysics, published by Copernicus Publ., Göttingen, Germania, vol. 17, pp. 809-815.
View web resourcesView DOI resources383
Piaggi P., Lippi C., Fierabracci P., Maffei M., Calderone A., Mauri M., Anselmino M., Cassano G., Vitti P., Pinchera, Landi A., and Santini F. (2010) “Artificial Neural Networks in the Outcome Prediction of Adjustable Gastric Banding in Obese Women”, PloS one, published by Public Library of Science, San Francisco, CA, Stati Uniti d'America, vol. 5, e13624 pages.
View DOI resources384
Pifferi M., Bush A., Pioggia G., Di Cicco M., Chinellato I., Bodini A., Macchia P., and Boner A. L. (2010) “Monitoring asthma control in allergic children by soft computing of lung function and exhaled nitric oxide”, Chest (Amer. Coll. Chest Phys. ), ISSN 0012-3692, published by The College, Chicago, Ill (Stati Uniti d'America), vol. Prepublished online October 7, 2010.
View web resourcesView DOI resources385
Ripoli A., Rainaldi G., Rizzo M., Mercatanti A., and Pitto L. (2010) “The Fuzzy Logic of MicroRNA Regulation: A Key to Control Cell Complexity”, Current genomics, ISSN 1389-2029, published by Bentham Science Publishers-Hilversum (Paesi Bassi), vol. 11(5), pp. 350-353.
View DOI resources386
Rossi M., Guzzetti F., Reichenbach P., Mondini A., and Peruccacci S. (2010) “Optimal landslide susceptibility zonation based on multiple forecasts”, Geomorphology (Amst. ), published by Elsevier, Oxford;, Paesi Bassi, vol. 114, pp. 129-142.
View web resourcesView DOI resources387
Tuci E., Massera G., and Nolfi S. (2010) “Active categorical perception of object shapes in a simulated anthropomorphic robotic arm”, IEEE transactions on evolutionary computation, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 14, pp. 885-899.
View web resourcesView DOI resources388
Varvarigou T., Tserpes K., Kyriazis D., Silvestri F., and Psimogiannos N. (2010) “A study on the effect of application and resource characteristics on the QOS in service provisioning environments”, International journal of distributed systems and technologies (Print), published by IGI Global, Hershey, PA, Stati Uniti d'America, vol. 1, pp. 55-75.
View DOI resources389
Alessandri A., Bolla R., Gaggero M., and Repetto M. (2009) “Modeling and identification of nonlinear dynamics for freeway traffic by using information from a mobile cellular network”, IEEE transactions on control systems technology (Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 17, pp. 952-959.
390
Ampatzis, C., Tuci, E., Trianni, V., Christensen, A. L., Dorigo, and M. (2009) “Evolving Self-Assembly in Autonomous Homogeneous Robots: Experiments with Two Physical Robots”, Artificial life, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 15(4), pp. 465-484.
View DOI resources391
Cirrincione M., Pucci M., Vitale G., and Miraoui A. (2009) “Current Harmonic Compensation by a Single-Phase Shunt Active Power Filter Controlled by Adaptive Neural Filtering”, IEEE transactions on industrial electronics (1982. Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 56.
392
Di Fatta G., Fiannaca A., Gaglio S., Rizzo R., and Urso A. (2009) “Clustering Quality and Topology Preservation in Fast Learning SOMs”, Neural Network World (Prague), published by Computer World Co., Prague, Repubblica Ceca, vol. 19-5, pp. 625-639.
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Di Garbo A. (2009) “Dynamics of a minimal neural model consisting of an astrocyte, a neuron, and an interneuron”, Journal of biological physics (Print), published by Kluwer Academic Publishers, Dordrecht;, Paesi Bassi, vol. 35, pp. 361-382.
View DOI resources394
Ferrari E. and Muselli M. (2009) “A multivariate algorithm for gene selection based on the nearest neighbor probability”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 5488, pp. 123-131.
View web resourcesView DOI resources395
Fuchs E., Ayali A., Ben Jacob E., and Boccaletti S. (2009) “The formation of synchronization cliques during the development of modular neural networks”, Physical biology (Print), published by IOP Publishing, Bristol, Regno Unito, vol. 6, 036018 pages.
View web resourcesView DOI resources396
Maddalena L. and Petrosino A. (2009) “3D Neural Model-Based Stopped Object Detection”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 5716, pp. 585-593.
View web resourcesView DOI resources397
Maddalena L. and Petrosino A. (2009) “Self Organizing and Fuzzy Modelling for Parked Vehicles Detection”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 5807, pp. 422-433.
View DOI resources398
Maddalena L. and Petrosino A. (2009) “Multivalued Background/Foreground Separation for Moving Object Detection”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 5571, pp. 263-270.
View web resourcesView DOI resources399
Madonna F., Russo F., Ware R., and Pappalardo G. (2009) “Mid-tropospheric supercooled liquid water observation consistent with nucleation induced by a mountain lee wave”, Geophysical research letters, published by American Geophysical Union., [Washington], Stati Uniti d'America, vol. 36, L18802 pages.
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Murari A., Vega J., Vagliasindi G., Alonso J. A., Alves D., Coelho R., Defiore S., Farthing J., Hidalgo C., Rattá G. A., and Jet Efda C. (2009) “Recent developments in data mining and soft computing for JET with a view on ITER”, Fusion engineering and design, published by North Holland., Amsterdam, Paesi Bassi, vol. 84, pp. 1372-1375.
View DOI resources401
Muselli M., Costacurta M., and Ruffino F. (2009) “Evaluating switching neural networks through artificial and real gene expression data”, Artificial intelligence in medicine (Print), published by Elsevier Science Publishers, Tecklenburg, Paesi Bassi, vol. 45, pp. 163-171.
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Olmi S., Livi R., Politi A., and Torcini A. (2009) “Partial synchronization in diluted neural networks”, BMC neuroscience (Online), published by BioMed Central, London, Regno Unito, vol. 10, P274 pages.
View web resources403
Paloscia S. and Santi E. (2009) “Global Scale analysis of soil moisture and vegetation biomass by using AMSR-E data”, Nihon Rimo¯to Senshingu Gakkaishi, published by Nihon Rimo¯to Senshingu Gakkai, Tokyo, Giappone, vol. 29, pp. 301-306.
404
Pasini A., Szpunar G., Amori G., Langone R., and Cristaldi M. (2009) “Assessing climatic influences on rodent density: a neural network modelling approach and a case study in Central Italy”, Asia-Pacific journal of atmospheric sciences (Print), published by Korean meteorological society, Seoul, Corea del Sud, vol. 45, pp. 319-330.
View DOI resources405
Pifferi M., Ragazzo V., Previti A., Pioggia G., Ferro M., Macchia P., Piacentini G., and Boner A. L. (2009) “Exhaled air temperature in asthmatic children: a mathematical evaluation”, Pediatric allergy and immunology, ISSN 0905-6157, published by Blackwell-Oxford (Regno Unito), vol. 20, pp. 164-171.
View DOI resources406
Taglialatela F., Cesario N., Lavorgna M., Me­rola S. S., and Vaglieco B. M. (2009) “Use of engine crankshaft speed for determination of cylinder pressure parameters”, SAE technical paper series, published by Society of Automotive Engineers, Warrendale, Penn., Stati Uniti d'America.
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Vagliasindi G., Murari A., Arena P., Fortuna L., and Mazzitelli G. (2009) “Cellular Neural Network Algorithms for Real-Time Image Analysis in Plasma Fusion”, IEEE transactions on instrumentation and measurement, published by Institute of Electrical and Electronics Engineers., New York, Stati Uniti d'America, vol. 58, pp. 2417-2425.
408
Zillmer R., Brunel N., and Hansel D. (2009) “Very long transients, irregular firing, and chaotic dynamics in networks of randomly connected inhibitory integrate-and-fire neurons”, vol. 79(3), 031909 pages.
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Alberga V., Satalino G., and Staykova D. K. (2008) “Comparison of polarimetric SAR observables in terms of classification performance”, International journal of remote sensing (Print), published by Taylor & Francis Ltd., London, Regno Unito, vol. 29, pp. 4129-4150.
View DOI resources410
Bystrenova E., Jelitai M., Tonazzini I., Lazar A. N., Huth M., Stoliar P., Dionigi C., Cacace M. G., Nickel N., Madarasz E., and Biscarini F. (2008) “Neural networks grown on organic semiconductors”, Advanced functional materials (Print), published by Wiley-VCH, Weinheim, Germania, vol. 18, pp. 1751-1756.
411
Calabretta, R, Di Ferdinando, A, Parisi, D, Keil, and F C. (2008) “How to learn multiple tasks”, Biological theory, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 3, pp. 30-41.
View DOI resources412
Carcano E. C., Bartolini P., Muselli M., and Piroddi L. (2008) “Jordan recurrent neural network versus IHACRES in modelling daily streamflows”, Journal of hydrology (Amst. ), published by Elsevier, Oxford;, Paesi Bassi, vol. 362, pp. 291-307.
413
Cervellera C., Macciò D., and Muselli M. (2008) “Deterministic learning for maximum likelihood estimation through neural networkss”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 19, pp. 1456-1467.
View DOI resources414
Cervellera C., Macciò D., and Muselli M. (2008) “Deterministic learning for maximum-likelihood estimation through neural networks”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 19, pp. 1456-1467.
View DOI resources415
De Gregorio M. (2008) “An Intelligent Active Video Surveillance System Based on the Integration of Virtual Neural Sensors and BDI Agents”, IEICE transactions on information and systems, published by Institute of Electronics, Information and Communication Engineers., Tokyo, Giappone, vol. E91, 1914 pages.
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Falavigna G. (2008) “A rating model simulation for risk analysis”, International journal of business performance management, published by Inderscience Enterprises, St. Helier, Jersey, Regno Unito, vol. 2/3, pp. 269-299.
View web resourcesView DOI resources417
Falavigna G. (2008) “An analysis of key-variables of default risk with complex systems”, International journal of business performance management, published by Inderscience Enterprises, St. Helier, Jersey, Regno Unito, vol. 2/3, pp. 202-230.
View web resourcesView DOI resources418
Falavigna G. (2008) “New contents and perspectives in the risk analysis of enterprises”, International journal of business performance management, published by Inderscience Enterprises, St. Helier, Jersey, Regno Unito, vol. 2/3, pp. 136-173.
View DOI resources419
Ferrari E. and Muselli M. (2008) “A constructive technique based on linear programming for training switching neural networks”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 5164, pp. 744-753.
View DOI resources420
Jekova I., Bortolan G., and Christov I. (2008) “Assessment and comparison of different methods for heart beat classification”, Medical engineering & physics, published by Butterworth-Heinemann, Oxford, Regno Unito, vol. 30, pp. 248-257.
421
Leone A. P., Calabrò G., Coppola E., Maffei C., Menenti M., Tosca M., Vella M., and Buondonno A. (2008) “Prediction of soil properties with VIS-NIR-SWIR reflectance spectroscopy and artificial neural networks. A case study”, vol. 39, pp. 685-698.
422
Leone A. P., Calabrò G., Coppola E., Maffei C., Menenti M., Tosca M., Vella M., and Buondonno A. (2008) “Prediction of soil properties with vis-nit-swir reflectance spectroscopy and artificial neural network: a case study of three pedoenvironments of the Campania Region, Italy”, Advances in geoecology, published by Catena Verlag, Germany, Germania, vol. 39, pp. 689-702.
View web resourcesView DOI resources423
Maddalena L. and Petrosino A. (2008) “A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications”, IEEE transactions on image processing, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 17, pp. 1168-1177.
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Maddalena L., Petrosino A., and Ferone A. (2008) “Object Motion Detection and Tracking by an Artificial Intelligence Approach”, International journal of pattern recognition and artificial intelligence, published by World Scientific., Singapore, Singapore, vol. 22, pp. 915-928.
View DOI resources425
Melchiorre C., Matteucci M., Azzoni A., and Zanchi A. (2008) “Artificial neural networks and cluster analysis in landslide susceptibility zonation”, Geomorphology (Amst. ), published by Elsevier, Oxford;, Paesi Bassi, vol. 94, pp. 379-400.
View DOI resources426
Mirolli M. and Parisi D. (2008) “How producer biases can favor the evolutionof communication: an analysis of evolutionary dynamics”, Adaptive behavior, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 16, pp. 27-52.
View DOI resources427
Moriondo M., Stefanini F. M., and Bindi M. (2008) “Reproduction of olive tree habitat suitability for global change impact assessment”, Ecological modelling, published by Elsevier, Shannon;, Paesi Bassi, vol. 218, pp. 95-109.
View DOI resources428
Muthu K., Petrou M., Tarantino C., and Blonda P. (2008) “Landslide Possibility Mapping Using Fuzzy Approaches”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 46, pp. 1253-1265.
429
Paloscia S., Pampaloni P., Pettinato S., and Santi E. (2008) “A Comparison of Algorithms for Retrieving Soil Moisture From ENVISAT/ASAR Images”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 46/10, pp. 3274-3284.
View DOI resources430
Pasini A. (2008) “External forcings and predictability in Lorenz model: An analysis via neural network modelling”, Il Nuovo cimento della Società italiana di fisica. C. Geophysics and space physics (Testo stamp. ), published by Editrice Compositori; [poi] Società italiana di fisica, Bologna, Italia, vol. 31, pp. 357-370.
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Passamonti L., Cerasa A., Mc G., Magariello A., Muglia M., Quattrone A., and Fera F. (2008) “Genetically-dependent modulation of serotonergic inactivation in the human prefrontal cortex”, NeuroImage (Orlando Fla., Print), published by Academic Press, Orlando, FL, Stati Uniti d'America, vol. 40, pp. 1264-1273.
432
Pellicioni A. and Tirabassi T. (2008) “Air pollution model and neural network: an integrated modelling system”, vol. 31, pp. 253-273.
View DOI resources433
Pioggia G., Ferro M., Di Francesco F., Ahluwalia A., and De Rossi D. (2008) “Assessment of bioinspired models for pattern recognition in biomimetic systems”, Bioinspiration & biomimetics (Print), ISSN 1748-3182, published by Institute of Physics Publishing., Bristol (Regno Unito), vol. 3(1).
434
Romani S., Amit D., and Amit Y. (2008) “Optimizing one-shot learning with binary Synapses”, Neural computation, published by MIT Press, Cambridge, Mass., Stati Uniti d'America, vol. 20, pp. 1928-1950.
View web resourcesView DOI resources435
Scozzari A. (2008) “Non-invasive methods applied to the case of Municipal Solid Waste landfills (MSW): analysis of long-term data”, Advances in geosciences (Print), published by Copernicus Publ., Göttingen, Germania, vol. 19, pp. 33-38.
436
Trombetti M., Riano D., Rubio M., Cheng Y., and Ustin S. (2008) “Multi-temporal vegetation canopy water content retrieval and interpretation using artificial neural networks for the continental USA”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 112, pp. 203-215.
View DOI resources437
Tuci E., Ampatzis C., Vicentini F., and Dorigo M. (2008) “Evolving homogeneous neurocontrollers for a group of heterogeneous robots: Coordinated motion, cooperation, and acoustic communication”, Artificial life, published by MIT Press, Cambridge, MA, Stati Uniti d'America, vol. 14, pp. 157-178.
438
???, ???, ??, ???, ???, Costabile F., ???, Bai X., Zhang Q., Fang D., Hong W., Liu F., Costabile F., and Wang F. (2007) “Application of Artificial Neural Network to Air Pollution Prediction in Suzhou City”, Zhongguo keji ziyuan daokan, published by Zhongguo Keji Ziyuan Daokan Zazhishe, Beijing, Cina, vol. 25, pp. 45-49.
View DOI resources439
Alessandri A., Cervellera C., and Sanguineti M. (2007) “Design of Asymptotic Estimators: An Approach Based on Neural Networks and Nonlinear Programming”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 18, pp. 86-96.
440
Bai X., Li H, Zhang Q., Costabile F., and Fang D. (2007) “Application of Artificial Neural Network to Air Pollution Prediction in Suzhou City”, vol. 25, pp. 45-49.
441
Bernacchia A. and Amit D. (2007) “Impact of spatiotemporally correlated images on the structure of memory”, Proceedings of the National Academy of Sciences of the United States of America, published by The Academy, Washington, D. C., Stati Uniti d'America, vol. 104, pp. 3544-3549.
View DOI resources442
Calabretta R. (2007) “Genetic interference reduces the evolvability of modular and nonmodular visual neural networks”, Philosophical transactions-Royal Society. Biological sciences (Print), published by Royal Society, London, Regno Unito, vol. 362, pp. 403-410.
View DOI resources443
Cervellera C., Wen A., and Chen V. C. P. (2007) “Neural Network and Regression Spline Value Function Approximations for Stochastic Dynamic Programming”, Computers & operations research, published by Pergamon, Toronto;, Regno Unito, vol. 34, pp. 70-90.
View DOI resources444
Ciarlini P. and Maniscalco U. (2007) “Wavelets and Elman neural networks for monitoring environmental variables”, Journal of computational and applied mathematics, published by Koninklijke Vlaamse Ingenieursvereniging, Amsterdam, Belgio, vol. 221, pp. 302-309.
View web resources445
Cirrincione G., Marsala G., Pucci M., and Cirrincione M. (2007) “The GMR Neural Network for Inverse Problems”, Journal of Electric Systems, vol. 3, pp. 176-188.
View DOI resources446
Cirrincione M., Pucci M., Cirrincione G., and Capolino G. (2007) “Sensorless Control of Induction Motors by Reduced Order Observer with MCA EXIN + Based Adaptive Speed Estimation”, IEEE transactions on industrial electronics (1982. Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 54, pp. 150-166.
View web resourcesView DOI resources447
Colantonio S., Benvenuti M., Di Bono M. G., Pieri G., and Salvetti O. (2007) “Object tracking in a stereo and infrared vision system”, Infrared physics & technology, published by Pergamon, Exeter, Regno Unito, vol. 49, pp. 266-271.
View DOI resources448
Coppini G., Miniati M., Paterni M., Monti S., and Ferdeghini E. M. (2007) “Computer-aided diagnosis of emphysema in COPD patients: Neural-network-based analysis of lung shape in digital chest radiographs”, Medical engineering & physics, ISSN 1350-4533, published by Butterworth-Heinemann, Oxford (Regno Unito), vol. 28, pp. 76-86.
449
Coraggio P. and De Gregorio M. (2007) “WiSARD and NSP for Robot Global Localization”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 4528, pp. 449-458.
450
Coraggio P. and De Gregorio M. (2007) “A Neurosymbolic Hybrid Approach for Landmark Recognition and Robot Localization”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 4729, pp. 566-575.
451
D'Orazio T., Leo M., Guaragnella C., and Distante A. (2007) “Analysis of image sequences for defect detection in composite materials”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 4678, pp. 855-864.
452
D'Orazio T., Leo M., Guaragnella C., and Distante A. (2007) “A visual approach for driver inattention detection”, Pattern recognition, published by Pergamon Press., New York, Regno Unito, vol. 40, pp. 2341-2355.
453
Di Fenza A., Alagona G., Ghio C., Leonardi R., Giolitti A., and Madami A. (2007) “Caco-2 cell permeability modelling: a neural network coupled genetic algorithm approach”, Journal of computer-aided molecular design, published by ESCOM Science Publishers, Leiden, Paesi Bassi, vol. 21, pp. 207-221.
View DOI resources454
Hender T. C., Wesley J. C., Bialek J., Bondeson A., Boozer A. H., Buttery R. J., Garofalo A., Goodman T. P., Granetz R. S., Gribov Y., Gruber O., Gryaznevich M., Giruzzi G., Günter S., Hayashi N., Helander P., Hegna C. C., Howell D. F., Humphreys D. A., Huysmans G. T. A., Hyatt A. W., Isayama A., Jardin S. C., Kawano Y., Kellman A., Kessel C., Koslowski H. R., La Haye R. J., Lazzaro E., Liu Y. Q., Lukash V., Manickam J., Medvedev S., Mertens V., Mirnov S. V., Nakamura Y., Navratil G., Okabayashi M., Ozeki T., Paccagnella R., Pautasso G., Porcelli F., Pustovitov V. D., Riccardo V., Sato M., Sauter O., Schaffer M. J., Shimada M., Sonato P., Strait E. J., Sugihara M., Takechi M., Turnbull A. D., Westerhof E., Whyte D. G., Yoshino R., and Zohm H. (2007) “Chapter 3: MHD stability, operational limits and disruptions”, Nuclear fusion, published by International Atomic Energy Agency., Wien, vol. 47, pp. S128-S202.
455
Incerti G., Feoli E., Salvati L., Brunetti A., and Giovacchini A. (2007) “Analysis of bioclimatic time series and their neural network-based classification to characterise drought risk patterns in South Italy”, International journal of biometeorology (Print), published by Swets & Zeitlinger, [Heidelberg];, Germania, vol. 51, pp. 253-263.
View DOI resources456
Infantino I., Rizzo R., and Gaglio S. (2007) “A framework for sign language sentence recognition by common sense context”, IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 37, pp. 1034-1039.
View web resourcesView DOI resources457
Kuzniz T., Halot D., Mignani A. G., Ciaccheri L., Kalli K., Tur M., Othonos A., Christofides C., and Jackson D. A. (2007) “Instrumentation for the monitoring of toxic pollutants in water resources by means of neural network analysis of absorption and fluorescence spectra”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 121, pp. 231-237.
View DOI resources458
Maddalena L. and Petrosino A. (2007) “A self-organizing approach to detection of moving patterns for real-time applications”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 4729, pp. 181-190.
View DOI resources459
Menenti, L., Burani, and C. (2007) “What causes the effect of age-of-acquisition in lexical processing?”, The quarterly journal of experimental psychology (2006. Print), published by Psychology Press, [Hove], Regno Unito, vol. 60, pp. 652-661.
460
Mirto M., Cafaro M., Fiore S., Tartarini D., and Aloisio G. (2007) “A Grid-enabled protein secondary structure predictor”, IEEE transactions on nanobioscience, published by Institute of Electrical and Electronics Engineers, Piscataway, NJ, Stati Uniti d'America, vol. 6, pp. 124-130.
461
Pellegrini G., De Arcangelis L., Herrmann H., and Perrone Capano C. (2007) “Activity-dependent neural network model on scale-free networks”, vol. 76, pp. 016107-016107.
462
Ruffino F., Costacurta M., and Muselli M. (2007) “Evaluating Switching Neural Networks for gene selection”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 4578, pp. 557-562.
View DOI resources463
Silvetti M., Pessa E., and Doricchi F. (2007) “Object-centred neglect: Simulation with head-centred coding based on Gaussian gaze-dependent units”, Neuropsychologia (Print), published by Pergamon Press., Oxford, Regno Unito, vol. 45, pp. 2553-2560.
464
Taglialatela S. F., Cesario N., Lavorgna M., Merola S. S., and Vaglieco B. M. (2007) “Soft computing model for prediction of EGR effects on particle sizing at CR Diesel engine exhaust”.
View DOI resources465
Tayfur G., Moramarco T., and Singh V. P. (2007) “Predicting and forecasting flow discharge at sites receiving significant lateral inflow”, Hydrological processes (Print), published by Wiley, Chichester, Sussex, England, Regno Unito, vol. 21, pp. 1848-1859.
466
Zani A., Rossi V., and Proverbio A. (2007) “The timing of cue-related activation of neural networks regulating visuo-spatial orienting”.
467
Zillmer R., Livi R., Politi A., and Torcini A. (2007) “Desynchronized stable states in diluted neural networks”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 70, 1960 pages.
468
Bai, X, Li, H, Zhang, Q, Costabile, F, Fang, and D (2006) “Progress of research on artificial neural network in air pollution prediction”, vol. 24 (1, pp. 77-81.
469
Boccaletti S., Latora V., Moreno Y., Chavez M., and Hwang D. (2006) “Complex Networks: Structure and Dynamics”, vol. 424, pp. 175-308.
470
Brunelli U., Piazza V., Pignato L., Filippo S., and Salvatore V. (2006) “Hourly Forecasting of SO2 Pollutant Concentration Using an Elman Neural Network”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 3931, pp. 65-69.
471
Cerasa A., Hagberg G., Peppe A., Bianciardi M., Gioia M., Costa A., Castriota Scanderbeg A., Caltagirone C., and Sabatini U. (2006) “Functional changes in the activity of cerebellum and frontostriatal regions during externally and internally timed movement in Parkinson's disease”, Brain research bulletin, published by ANKHO International Inc., Phoenix, N. Y., Stati Uniti d'America, vol. 71, pp. 259-269.
View DOI resources472
Cervellera C., Chen V. C. P., and Wen A. (2006) “Optimization of a large-scale water reservoir network by stochastic dynamic programming with efficient state space discretization”, European journal of operational research, published by Elsevier, Amsterdam, Paesi Bassi, vol. 171, pp. 1139-1151.
View DOI resources473
Cirrincione M., Pucci M., Cirrincione G., and Capolino G. (2006) “An Adaptive Speed Observer Based on a New Total Least-Squares Neuron for Induction Machine Drives”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America, vol. 42, pp. 89-104.
474
Depari A., Ferrari P., Ferrari V., Flammini A., Ghisla A., Marioli D., and Taroni A. (2006) “Digital signal processing for biaxial position measurement with a pyroelectric sensor array”, IEEE transactions on instrumentation and measurement, published by Institute of Electrical and Electronics Engineers., New York, Stati Uniti d'America, vol. 55, pp. 501-506.
475
Falavigna G. (2006) “Models for Default Risk Analysis: Focus on Artificial Neural Networks, Model Comparisons, Hybrid Frameworks”, Working paper (CERIS, Ist. ric. impresa sviluppo), published by Consiglio nazionale delle ricerche, Torino, Italia.
View DOI resources476
Gentili G. B., Riminesi C., and Tesi V. (2006) “Low cost microwave sensor for moisture content measurement in paper milling industry”, Sensing and imaging, published by Springer, New York, NY, Stati Uniti d'America, vol. 7, pp. 155-173.
477
Marmo R. and Amodio S. (2006) “A Neural Network for classification of chambers arrangement in foraminifera”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 2955, pp. 271-278.
478
Mohanty P. K. and Politi A. (2006) “A new approach to partial synchronization in globally coupled rotators”, Journal of physics. A, mathematical and general (Print), published by IOP Publishing, Bristol, Regno Unito, vol. 39, L415 pages.
View DOI resources479
Moriondo M. and Bindi M. (2006) “Comparison of temperatures simulated by GCMs, RCMs and statistical downscaling: potential application in studies of future crop development”, Climate research, published by Inter-Research., Oldendorf/Luhe, Germania, vol. 30, pp. 149-160.
View DOI resources480
Muselli M. (2006) “Switching neural networks: A new connectionist model for classification”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 3931, pp. 23-30.
View DOI resources481
Pardo M., Sisk B., Sberveglieri G., and Lewis N. (2006) “Comparison of Fisher's linear discriminant to multilayer perceptron networks in the classification of vapors using sensor array data”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 115, pp. 647-655.
View DOI resources482
Pasini A., Lorè M., and Ameli F. (2006) “Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system”, Ecological modelling, published by Elsevier, Shannon;, Paesi Bassi, vol. 191, pp. 58-67.
483
Pelliccioni A. and Tirabassi T. (2006) “Air dispersion model and neural network: a new perpective for integrated models in the simulation of complex situations”, Environmental modelling & software, published by Elsevier, Oxford, Regno Unito, vol. 21, 00, pp. 539-546, 00.
View web resourcesView DOI resources484
Pereira F., Stuer H., Castano Graff E., and Gharib M. (2006) “Two-Frame 3D Particle Tracking”, Measurement science & technology (Print), published by IOP Publishing, Bristol, Regno Unito, vol. 17, pp. 1680-1692.
View DOI resources485
Pioggia G., Ferro M., Di Francesco F., and De Rossi D. (2006) “A processing architecture for associative short-term memory in electronic noses”, Measurement science & technology (Print), ISSN 0957-0233, published by IOP Publishing, Bristol (Regno Unito), vol. 17(11), pp. 3066-3072.
View web resourcesView DOI resources486
Piraino P., Ricciardi A., Salzano G., Zotta T., and Parente E. (2006) “Use of unsupervised and supervised artificial neural networks for the identification of lactic acid bacteria on the basis of SDS-PAGE patterns of whole cell proteins”, Journal of microbiological methods, published by Elsevier Science Ireland, Shannon, Paesi Bassi, vol. 66, pp. 336-346.
487
Tarantino C., D'Addabbo A., Castellana L., Blonda P., Pasquariello G., Ancona N., and Satalino G. (2006) “Neural network ensemble and support vector machine classifiers: An application to remote sensed data”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 2955, pp. 317-323.
View DOI resources488
Zillmer R., Livi R., Politi A., and Torcini A. (2006) “Desynchronization in diluted neural networks”, Physical review. E, Statistical, nonlinear, and soft matter physics (Print), published by Published by the American Physical Society through the American Institute of Physics, Melville, NY, Stati Uniti d'America, vol. 74, 036203 pages.
View DOI resources489
Armano G., Mancosu G., Milanesi L., Orro A., Saba M., and Vargiu E. (2005) “A hybrid genetic-neural system for predicting protein secondary structure”, BMC bioinformatics, published by BioMed Central, [London], Regno Unito, vol. 6.
490
Benvenuti M., Colantonio S., Di Bono M. G., Pieri G., and Salvetti O. (2005) “Tracking of Moving Targets in Video Sequences”, WSEAS transactions on systems, published by WSEAS Press, Athens, vol. 4, pp. 359-364.
491
Boschetti M., Gallo I., Brivio P. A., and Binaghi E. (2005) “Spectral/spatial data fusion by neural network techniques to retrieve vegetation understory information”, vol. 33/34, pp. 47-59.
View web resources492
Chillemi S., Panarese A., Barbi M., and Di Garbo A. (2005) “Gap-junctions promote synchrony in a network of inhibitory interneurons in the presence of heterogeneities and noise”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 3561, pp. 77-85.
View DOI resources493
Cicirelli G., D'Orazio T., and Distante A. (2005) “Different learning methodologies for vision-based navigation behaviors”, International journal of pattern recognition and artificial intelligence, published by World Scientific., Singapore, Singapore, vol. 19, pp. 1-26.
View web resources494
Cirrincione M., Cirrincione G., Pucci M., and Simoes M. (2005) “A Neural Non-linear Predictive Control for PEM-FC”, Journal of Electric Systems, vol. 1.
View DOI resources495
Cirrincione M. and Pucci M. (2005) “An MRAS Speed Sensorless High Performance Induction Motor Drive with a Predictive Adaptive Model”, IEEE transactions on industrial electronics (1982. Print), published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 52.
View DOI resources496
Cirrincione M. and Pucci M. (2005) “Sensorless Direct Torque Control of an Induction Motor by a TLS based MRAS Observer with Adaptive Integration”, Automatica (Oxf. ), published by Pergamon, Oxford [etc. ], Regno Unito, vol. 41.
497
Colantonio S., Di Bono M. G., and Pieri G. (2005) “Processing multimedia biomedical information for disease evolution monitoring”, ERCIM news, published by ERCIM., Le Chesnay, vol. 60, pp. 28-29.
498
Colantonio S., Salvetti O., and Sartucci F. (2005) “Automatic recognition and classification of cerebral microemboli in ultrasound images”, Pattern recognition and image analysis, published by Distributed by Allen Press, Lawrence, KS, Stati Uniti d'America, vol. 15-2, pp. 532-535.
View DOI resources499
D'Orazio T., Guaragnella C., Leo M., and Spagnolo P. (2005) “Defect Detection in Aircraft Composites by Using a Neural Approach in the Analysis of Thermographic Images”, NDT & E international, published by Butterworth-Heinemann, Oxford, Regno Unito, vol. 38, pp. 665-673.
View web resourcesView DOI resources500
Dalla Marta A., De Vincenzi M., Dietrich S., and Orlandini S. (2005) “Neural network for the estimation of leaf wetness duration: application to a Plasmopara viticola infections forecasting”, Physics and chemistry of the earth. Parts A/B/C (Online), published by Elsevier Science, [New York], Paesi Bassi, vol. 30, pp. 91-96.
501
Dalla Marta A., M D. V., S D., and S O. (2005) “Neural network estimation of leaf wetness duration: application to a Plasmopara viticola infection forecasting”, Physics and chemistry of the earth (2002), published by Elsevier Science., Kidlington, Regno Unito, vol. 30, pp. 91-96, 00.
502
Luchetta A., Serio C., and Viggiano M. (2005) “A soft computing approach to the elaboration of satellite data”, Fuzzy Systems and A. I. Reports and Letters, published by Editura Academiei Române., Iasi, Romania, vol. 11, pp. 45-52.
503
Marmo R., Amodio S., Tagliaferri R., Ferreri V., and Longo G. (2005) “Textural identification of carbonate rocks by image processing and neural network: methodology proposal and examples”, Computers & geosciences, published by Pergamon Press., New York, Regno Unito, vol. 31, pp. 649-659.
View web resourcesView DOI resources504
Marzano F. S., Cimini D., Coppola E., Verdecchia M., Levizzani V., Tapiador F., and Turk F. J. (2005) “Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale”, Advances in geosciences (Online), published by Copernicus Publ., Göttingen, Germania, vol. 2, pp. 267-272.
View DOI resources505
Murari A., Joffrin E., Felton R., Mazon D., Zabeo L., Albanese R., Arena P., Ambrosino G., Ariola M., Barana O., Bruno M., Laborde L., Moreau D., Piccolo F., Sartori F., Crisanti F., De La Luna E., and Sanchez J. (2005) “Development of real-time diagnostics and feedback algorithms for JET in view of the next step”, Plasma physics and controlled fusion (Print), published by Institute of Physics, Bristol, Regno Unito, vol. 47, pp. 395-407.
View DOI resources506
Pelosi G., Pinto A., Riminesi C., Selleri S., and Tatini M. (2005) “Fast interelement coupling analysis in finite arrays”, Microwave and optical technology letters (Print), published by Wiley, New York, Stati Uniti d'America, vol. 47, pp. 155-158.
507
Penza, M., Cassano, G., Aversa, P., Cusano, A., Cutolo, A., Giordano, M., Nicolais, and L. (2005) “Carbon nanotube acoustic and optical sensors for volatile organic compound detection”, Nanotechnology (Bristol. Print), published by IOP Publishing, Bristol, Regno Unito, vol. 16, pp. 2536-2547.
View DOI resources508
Rizzo R. (2005) “A high-order graph generating self-organizing structure”, International journal of neural systems, published by World Scientific., Singapore, Singapore, vol. 15, pp. 349-355.
509
Stuart, L. J., Marocco, D., Cangelosi, and A. (2005) “Information Visualization for Knowledge Extraction in Neural Networks”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 3697, pp. 515-520.
View web resourcesView DOI resources510
Ungaro F., Calzolari C., and Busoni E. (2005) “Development of pedotransfer functions using a group method of data handling for the soil of the Pianura Padano-Veneta region of North Italy. Water retention properties”, Geoderma (Amst. ), published by Elsevier., Oxford;, Paesi Bassi, vol. 124, pp. 293-317.
511
Aiello G., Gaglio S., Lo Re G., and Urso A. (2004) “A Random Neural Network for the Dynamic Multicast Problem”, WSEAS transactions on computers, published by WSEAS Press, Athens, vol. 3-5, pp. 1545-1550.
512
Alessandri A. (2004) “Adaptive Neural Network Control of Robotic Manipulators”, Automatica (Oxf. ), published by Pergamon, Oxford [etc. ], Regno Unito, vol. 40, pp. 2011-2012.
513
Alfredo P. and Marco G. (2004) “Encoding Nondeterministic Fuzzy Tree Automata into Recursive Neural Networks”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 15-6, pp. 1435-1449.
View web resources514
Arca B., Duce P., Spano D., Snyder R. L., and Fiori M. (2004) “Use of Numerical Weather Forecast and Time Series Models for Predicting Reference Evapotranspiration”, Acta horticulturae, published by International Society for Horticultural Science., The Hague, vol. 664, pp. 39-46.
View DOI resources515
Binaghi E., Boschetti M., Brivio P. A., Gallo I., Pergalani F., and Rampini A. (2004) “Prediction of displacements in unstable areas using a neural model”, Natural hazards (Dordr. ), published by Kluwer Academic Pubishers, Boston, Paesi Bassi, vol. 321, pp. 137-156.
View DOI resources516
Bocchi L., Coppini, G., Nori J., and Valli G. (2004) “Detection of single and clustered microcalcifications in mammograms using fractals models and neural network”, Medical engineering & physics, ISSN 1350-4533, published by Butterworth-Heinemann, Oxford (Regno Unito), vol. 26(4), pp. 303-312.
517
Bresciani E., Menchetti A., Bozzi A., and Fedele G. (2004) “Sistema di filologia computazionale per testi demotici”, Archeologia e calcolatori, ISSN 1120-6861, published by All'Insegna del giglio-Firenze (Italia), vol. 15, pp. 267-286.
View DOI resources518
Bulone D., Giacomazza D., Monge M. E., Negri R. M., and Bernik D. L. (2004) “Electronic Nose screening of limonene release from multicomponent essential oils encapsulated in pectin gels”, Combinatorial chemistry & high throughput screening (Print), published by Bentham Science Publishers, Hilversum, Paesi Bassi, vol. 7, pp. 337-344.
View DOI resources519
Calabretta R., Di Ferdinando A., and Parisi D. (2004) “Ecological neural networks for object recognition and generalization”, Neural Processing Letters, published by D facto s. a., Bruxelles, Belgio, vol. 19, pp. 37-48.
520
Cangelosi A. and Parisi D. (2004) “The processing of verbs and nouns in neural networks: Insights from synthetic brain imaging”, Brain and language (Print), published by Academic Press., San Diego [etc. ], Stati Uniti d'America, vol. 89, pp. 401-408.
View DOI resources521
Cervellera C. and Muselli M. (2004) “Deterministic design for neural network learning: An approach based on discrepancy”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 15, pp. 533-544.
View DOI resources522
Christov I. and Bortolan G. (2004) “Ranking of pattern recognition parameters for premature ventricular contractions classification by neural networks”, Physiological measurement (Print), published by Institute of Physics Publishing., Bristol, Regno Unito, vol. 24, pp. 1281-1290.
View DOI resources523
Cirrincione M., Pucci M., Cirrincione G., and Capolino G. A. (2004) “A New Adaptive Integration Methodology for Estimating Flux in Induction Machine Drives”, IEEE transactions on power electronics, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 19.
View DOI resources524
Cirrincione M., Pucci M., Cirrincione G., and Capolino G. A. (2004) “A New TLS Based MRAS Speed Estimation with Adaptive Integration for High Performance Induction Motor Drives”, IEEE transactions on industry applications, published by Institute of Electrical and Electronic Engineers], [New York, Stati Uniti d'America.
View DOI resources525
Coppini G., Diciotti S., and Valli G. (2004) “Matching of medical images by self-organizing neural networks”, Pattern recognition letters, ISSN 0167-8655, published by North-Holland-Amsterdam (Paesi Bassi), vol. 25(3), pp. 341-352.
526
Coppini G., Diciotti, G., and Valli G. (2004) “Matching of medical images by self organizing neural networking”, Pattern recognition, ISSN 0031-3203, published by Pergamon Press, New York (Regno Unito), vol. 19, 5, pp. 333-339.
527
Di Bono M. G., Pieri G., and Salvetti O. (2004) “A tool for system monitoring based on artificial neural networks”, WSEAS transactions on systems, published by WSEAS Press, Athens, vol. 3, pp. 746-751.
528
Garcia González D. L., Mannina L., D'Imperio M., Segre A. L., and Aparicio R. (2004) “Using 1H and 13C NMR and Artificial Neural Networks to Detect the Adulteration of Olive Oil with Hazelnut Oil”, vol. 219, pp. 545-548.
529
Luchetta A., Telesca L., and Viggiano M. (2004) “A Neural Network approach to estimate the magnitude of forthcoming earthquakes”, Geophysical research abstracts (Online), published by Copernicus GmbH, Katlenburg-Lindau, Germania, vol. 6.
View DOI resources530
Mazzeo P. L., Nitti M., Stella E., and Distante A. (2004) “Visual Recognition of Fastening Bolts for Railroads Maintenance”, Pattern recognition letters, published by North-Holland, Amsterdam, Paesi Bassi, vol. 25, pp. 669-677.
View DOI resources531
Monge M. E., Bulone D., Giacomazza D., Bernik D. L., and Negri R. M. (2004) “Detection of flavour release from pectin gels using electronic noses”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 101, pp. 28-38.
532
Monge M., Bulone D., Giacomazza D., Negri M., and Bernik D. (2004) “electronic nose screening of limonene release from multicomponent essential oils encapsulated in pectin gels”, Combinatorial chemistry & high throughput screening (Print), published by Bentham Science Publishers, Hilversum, Paesi Bassi, vol. 7, pp. 335-342.
533
Pilato G., Vitabile S., Vassallo G., Conti V., and Sorbello F. (2004) “Web Directories as a Knowledge Base to Build a Multi-Agent System for Information Sharing”, Web intelligence and agent systems, published by IOS Press, Washington, DC, Paesi Bassi, vol. 2, pp. 265-277.
View web resourcesView DOI resources534
Tapiador F. J., Kidd C., Levizzani V., and Marzano F. S. (2004) “A Neural Networks-Based Fusion Technique to Estimate Half-Hourly Rainfall Estimates at 0. 18 Resolution from Satellite Passive Microwave and Infrared Data”, Journal of applied meteorology (1988), published by American Meteorological Society, Boston, MA, Stati Uniti d'America, vol. 43, pp. 576-594.
535
Tedesco M., Pulliainen J., Takala M., Hallikainen M., and Pampaloni P. (2004) “'Artificial Neural Network based techniques for the retrieval of SWE and snow depth from SSM/I data'”, Remote sensing of environment, published by American Elsevier Pub. Co., New York, Stati Uniti d'America, vol. 90, pp. 76-85.
536
Tonazzini A., Vezzosi S., and Bedini L. (2004) “Analysis and recognition of highly degraded printed characters”, International journal on document analysis and recognition (Internet), published by Springer., Heidelberg, Germania, vol. 6, pp. 236-247.
View DOI resources537
Zuppa M., Distante C., Siciliano P., and Persaud K. (2004) “Drift counteraction with multiple self-organising maps for an electronic nose”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 98, pp. 305-317.
538
Alessandri A. (2003) “Fault diagnosis for nonlinear systems using a bank of neural estimators”, Computers in industry, published by Elsevier, Amsterdam, Paesi Bassi, vol. 52, pp. 271-289.
View DOI resources539
Amato U., Larobina M., Antoniadis A., and Alfano B. (2003) “Segmentation of magnetic resonance brain images through discriminant analysis”, Journal of neuroscience methods, published by Elsevier, Shannon;, Paesi Bassi, vol. 131, pp. 65-74.
540
Barcaro U., Di Bona S., Fontanelli R., La Manna S., Orlandi G., Salvetti O., and Sartucci F. (2003) “Real-time detection and clinical categorisation of ultrasound high intensity transient signal”, WSEAS transactions on systems, published by WSEAS Press, Athens, vol. 2, pp. 921-926.
541
Binaghi E., Gallo I., and Pepe M. (2003) “A Neural Adaptive Model for Feature Extraction and Recognition in High Resolution Remote Sensing Imagery”, International journal of remote sensing (Print), published by Taylor & Francis Ltd., London, Regno Unito, vol. 24, pp. 3947-3959.
View DOI resources542
Brivio P. A., Maggi M., Binaghi E., and Gallo I. (2003) “Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification”, International journal of remote sensing (Print), published by Taylor & Francis Ltd., London, Regno Unito, vol. 24, pp. 4003-4018.
543
Calabretta R., Di Ferdinando A., Wagner G. P., and Parisi D. (2003) “What does it take to evolve behaviorally complex organisms?”, Biosystems (Amst. Print), published by Elsevier Science Ireland, Shannon, Paesi Bassi, vol. 69, pp. 245-262.
544
Cervellera C. and Muselli M. (2003) “A deterministic learning approach based on discrepancy”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 2859, pp. 53-60.
View DOI resources545
Chimenti M., De Rossi D., Di Francesco F., Domenici C., Pioggia G., Pieri G., and Salvetti O. (2003) “A neural approach for improving the measurement capability of an electronic nose”, Measurement science & technology (Print), ISSN 0957-0233, published by IOP Publishing, Bristol (Regno Unito), vol. 14(6), pp. 815-821.
View web resourcesView DOI resources546
Cicirelli G., D'Orazio T., and Distante A. (2003) “Target recognition by components for mobile robot navigation”, Journal of experimental and theoretical artificial intelligence (Print), published by Taylor & Francis, London, Regno Unito, vol. 15, pp. 281-297.
547
Cirrincione G. and Cirrincione M. (2003) “A novel self-organizing neural network for motion segmentation”, Applied intelligence (Boston), published by Kluwer Academic Publishers, London;, Stati Uniti d'America, vol. 18, pp. 27-35.
548
Cirrincione M. and Serporta C. (2003) “SPEED ESTIMATION IN INDUCTION MOTOR DRIVES USING THE PROGRESSIVE LEARNING NEURAL NETWORK (PLN)”, vol. 15, pp. 28-32.
549
Conti V., Pilato G., Sorbello F., Vassallo G., and Vitabile S. (2003) “A Concurrent Neural Classifier for HTML Documents Retrieval”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 2859, pp. 210-217.
550
Coppini G., Diciotti S., Falchini M., Villari N., and Valli G. (2003) “Neural Networks for Computer-Aided Diagnosis: Detection of Lung Nodules in Chest Radiograms”, IEEE transactions on information technology in biomedicine, ISSN 1089-7771, published by Institute of Electrical and Electronics Engineers, New York, NY (Stati Uniti d'America), vol. 7, pp. 344-357.
View web resourcesView DOI resources551
Di Bona S., Niemann H., Pieri G., and Salvetti O. (2003) “Brain volumes characterization using hierarchical neural networks”, Artificial intelligence in medicine (Print), published by Elsevier Science Publishers, Tecklenburg, Paesi Bassi, vol. 28, pp. 307-322.
552
Di Bona S. and Salvetti O. (2003) “A multilevel neural approach to dynamic scene analysis”, Pattern recognition and image analysis, published by Distributed by Allen Press, Lawrence, KS, Stati Uniti d'America, vol. 13, pp. 86-89.
553
Di Bona S. and Salvetti O. (2003) “Automatic monitoring of states evolution in dinamic scene supervision”, Pattern recognition and image analysis, published by Distributed by Allen Press, Lawrence, KS, Stati Uniti d'America, vol. 13, pp. 495-504.
554
Hariri A., Mattay V., Tessitore A., Fera F. -., and Weinberger D. (2003) “Neocortical modulation of the amygdala response to fearful stimuli”, Biological psychiatry (1969), published by Elsevier [etc. ], [New York], Stati Uniti d'America, vol. 53, pp. 494-501.
555
Kuruoglu E. E., Bedini L., Paratore M. T., Salerno E., and Tonazzini A. (2003) “Source separation in astrophysical maps using independent factor analysis”, Neural networks, published by Pergamon, New York, Stati Uniti d'America, vol. 16, pp. 479-491.
556
Lefik, M., and Schrefler B. A. (2003) “Artificial neural network as an incremental non-linear constitutive model”, Computer methods in applied mechanics and engineering, published by North-Holland, Amsterdam, Paesi Bassi, vol. 192, pp. 3265-3283.
557
Leo M., Spagnolo P., Attolico G., and Distante A. (2003) “Shape Based People Detection for Visual Surveillance Systems”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 2688, pp. 285-293.
558
Paloscia S., Macelloni G., Santi E., and Tedesco M. (2003) “An Application of Artificial Neural Networks for the Retrieval of Soil Moisture Profiles by using Microwave Radiometers”, Rivista italiana di telerilevamento (Online), published by Associazione Italiana di Telerilevamento, Firenze, Italia, vol. 26-28, pp. 57-62.
559
Pasini A. and Ameli F. (2003) “Radon short range forecasting through time series preprocessing and neural network modeling”, Geophysical research letters, published by American Geophysical Union., [Washington], Stati Uniti d'America, vol. 30.
560
Pasini A., Perrino C., and Zujic A. (2003) “Non-linear atmospheric stability indices by neural network modelling”, Il Nuovo cimento della Società italiana di fisica. C. Geophysics and space physics (Testo stamp. ), published by Editrice Compositori; [poi] Società italiana di fisica, Bologna, Italia, vol. 26, pp. 633-638.
561
Pellicioni A., Gariazzo C., and Tirabassi T. (2003) “Coupling of neural network and dispersion models: a novel methodology for air pollution models”, vol. 20, pp. 1-6.
562
Pieri G. and Salvetti O. (2003) “Scene understanding using hierarchical neural networks”, ERCIM news, published by ERCIM., Le Chesnay, vol. 52, pp. 52-52.
563
Rodriguez R., Lansky P., and Di Maio V. (2003) “Vesicular mechanisms and estimates of firing probability in a network of spiking neurons”, Physica. D, Nonlinear phenomena (Print), published by North-Holland, Amsterdam, Paesi Bassi, vol. 181, pp. 132-145.
564
Sandak J. and Tanaka C. (2003) “Online adaptive control of bandsaw feed speed using a fuzzy-neural system”, Forest products journal, published by Forest Products Society., Madison, Wis., Stati Uniti d'America, vol. 53, 6, pp. 36-43.
View DOI resources565
Taurino A. M., Distante C., Siciliano P., and Vasanelli L. (2003) “Quantitative and qualitative analysis of VOCs mixtures by means of a microsensors array and different evaluation methods”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 93, pp. 117-125.
566
Alderighi M. (2002) “Processing of csi(Tl) 2D-Matrices by means of Neural Networks and Markov Random Fields”, IEEE transactions on nuclear science, published by Professional Technical Group on Nuclear Science, New York, N. Y., Stati Uniti d'America, vol. 49, pp. 1661-1668.
567
Alessandri A., Sanguineti M., and Maggiore M. (2002) “Optimization-based learning with bounded error for feedforward neural networks”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 13, pp. 261-273.
View DOI resources568
Arrigo P., Scartezzini P., and Romano P. (2002) “AgeWa: an integrated approach for antisense experiment design”, IEEE transactions on nanobioscience, published by Institute of Electrical and Electronics Engineers, Piscataway, NJ, Stati Uniti d'America, vol. 1, pp. 167-171.
569
Barana O. and Manduchi G. (2002) “Application of Neural Networks for the Measurement of Electronic Temperature in Nuclear Fusion Experiments”, Neural computing & applications (Print), published by Springer., Godalming, Regno Unito, vol. 10, 351 pages.
570
Barana O., Murari A., Franz P., Ingesson L. C., and Manduchi G. (2002) “Neural networks for real time determination of radiated power in JET”, Review of scientific instruments, published by American Institute of Physics, [Woodbury, N. Y. ], Stati Uniti d'America, vol. 73, 2038 pages.
571
Bartolomeo P., Pagliarini L., and Parisi D. (2002) “Emergence of orienting behavior in ecological neural networks”, Neural Processing Letters, published by D facto s. a., Bruxelles, Belgio, vol. 15, pp. 69-76.
View web resourcesView DOI resources572
Bortolan G. and Pedrycz W. (2002) “Linguistic neurocomputing: the design of a neural networks in the framework of fuzzy sets”, Fuzzy sets and systems, published by North-Holland, Amsterdam, Paesi Bassi, vol. 128, pp. 389-412.
573
Chella A., Frixione M., and Gaglio S. (2002) “Anchoring symbols to conceptual spaces: the case of dynamic scenarios”, Robotics and autonomous systems (Print), published by North Holland, Amsterdam, Paesi Bassi.
574
Dammone G. B., Antonio G., Filippo S., and Salvatore V. (2002) “MLP Neural Network Implementation on a SIMD Architecture”, Lecture notes in computer science, published by Springer, Berlin, Germania, vol. 2486, pp. 99-108.
575
Di Bona S., Niemann H., Salvetti O., and Wolf M. (2002) “Computational complexity analysis of a 3D neural network approach to volume matching”, Pattern recognition, published by Pergamon Press., New York, Regno Unito, vol. 12, pp. 63-69.
View DOI resources576
Di Bona S. and Salvetti O. (2002) “Neural Method for three-dimensional image matching”, Journal of electronic imaging (Print), published by IS&T-Society for Imaging Science and Technology., Springfield, vol. 11, pp. 497-506.
View DOI resources577
Distante C., Leo M., Siciliano P., and Persaud K. C. (2002) “On the study of feature extraction methods for an electronic nose”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 87, pp. 274-288.
578
Drago G. P., Licitra L., Setti E., and Liberati D. (2002) “Forecasting the performance status of head and neck cancer patient treatment by an interval arithmetic pruned perceptron”, IEEE transactions on biomedical engineering (Print), published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 49, pp. 782-787.
View DOI resources579
Drago G., Setti E., Licitra L., and Liberati D. (2002) “Forecasting the performance status of head and neck cancer patient treatment by an interval arithmetic, pruned perceptron”, IEEE transactions on biomedical engineering (Print), published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 49, pp. 782-787.
580
Liu, Chandrasekar H., Gorgucci V., and E. (2002) “Detection of rain/no rain condition on the ground based on radar observations”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 30, pp. 696-699.
581
Nolfi S. (2002) “Power and Limits of Reactive Agents”, Neurocomputing (Amst. ), published by Elsevier Science Publishers, Amsterdam, Paesi Bassi, vol. 42, pp. 119-145.
582
Olmi R., Pelosi G., Riminesi C., and Tedesco M. (2002) “A neural network approach to real-time dielectric characterization of materials”, Microwave and optical technology letters (Print), published by Wiley, New York, Stati Uniti d'America, vol. 35, pp. 463-465.
View DOI resources583
Satalino G., Mattia F., Davidson M. W. J., Le Toan T., Pasquariello G., and Borgeaud M. (2002) “On current limits of soil moisture retrieval from ERS-SAR data”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 40, pp. 2438-2447.
584
Viginio C. and Alfredo P. (2002) “Neural Recognition in a Pyramidal Structure”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 13-2, pp. 472-480.
585
Alessandri A., Parisini T., and Zoppoli R. (2001) “Sliding-window neural state estimation in a power plant heater Sliding-window neural state estimation in a power plant heater line”, International journal of adaptive control and signal processing (Print), published by Wiley, New York, Regno Unito, vol. 15, pp. 815-836.
View web resourcesView DOI resources586
Angelini L., De Carlo F., Marangi C., Mannarelli M., Nardulli G., Pellicoro M., Satalino G., and Tramaglia S. S. (2001) “Chaotic neural network clustering: an application to landmine detection by dynamic infrared imaging”, Optical engineering (Bellingham, Print), published by Society of Photo-optical Instrumentation Engineers., Bellingham, WA, vol. 40, pp. 2878-2884.
587
Baldassarre G. (2001) “Cultural evolution of 'guiding criteria' and behaviour in a population of neural-network agents”, Journal of memetics-evolutionary models of information transmission, published by Centre for Policy Modelling., Manchester, Regno Unito, vol. 4.
View DOI resources588
Baraldi A., Binaghi E., Blonda P., Brivio P. A., and Rampini A. (2001) “A Detailed Comparison of Neuro-Fuzzy Estimation of Sub-pixel Land-Cover Composition from Remotely Sensed Data”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 39, pp. 994-1005.
589
Baraldi A., Binaghi E., Blonda P., Brivio P. A., and Rampini A. (2001) “Comparison of the Multilayer Perceptron with Neuro-Fuzzy Techniques in the estimation of cover class mixture in remotely sensed data”, IEEE transactions on geoscience and remote sensing, published by Institute of Electrical and Electronics Engineers, New York, N. Y., Stati Uniti d'America, vol. 39, pp. 994-1005.
View web resourcesView DOI resources590
Barana O., Manduchi G., Serri A., and Sonato P. (2001) “A neural network approach for the detection of the locking position in RFX”, Fusion engineering and design, published by North Holland., Amsterdam, Paesi Bassi, vol. 55, pp. 9-20.
591
Bindi M. and Maselli F. (2001) “Extension of crop model outputs over the land surface by the application of statistical and neural network techniques to topographical and satellite data”, Climate research, published by Inter-Research., Oldendorf/Luhe, Germania, vol. 16, pp. 237-246.
592
Buzzi C., Grippo L., and Sciandrone M. (2001) “Convergent Decomposition Techniques for Training {RBF} Neural Networks”, Neural computation, published by MIT Press, Cambridge, Mass., Stati Uniti d'America, vol. 13, pp. 1891-1920.
593
Cappa C., Anfossi D., Grosa M. M., and Natale P. (2001) “Short term predictions of urban NO2 pollution by means of artificial neural networks”, vol. 15, pp. 483-496.
594
Di Ferdinando A., Calabretta R., and Parisi D. (2001) “Evolving modular architectures for neural networks”, Perspectives in neural computing, published by Springer., Berlin;, Regno Unito, pp. 253-262.
595
Guerriero L., Refice A., Stramaglia S., Satalino G., Veneziani N., Blonda P., Pasquariello G., and Chiaradia M. (2001) “Global approaches and local strategies for phase unwrapping”, Nuovo cimento della Società italiana di fisica. C, published by Editrice Compositori, Bologna, Italia, vol. 24, pp. 205-222.
596
Lampariello F. and Sciandrone M. (2001) “Efficient Training of {RBF} Neural Networks for Pattern Recognition”, IEEE transactions on neural networks, published by Institute of Electrical and Electronics Engineers, New York, NY, Stati Uniti d'America, vol. 12, pp. 1235-1242.
597
Morgavi G., Morando M., and Baratta D. (2001) “Music rhythm recognition through feature extraction and neural networks”, CASYS: international journal of computing anticipatory systems, published by CHAOS., Liège, Belgio, vol. 8, pp. 115-127.
598
Moro A., Tettamanti M., Perani D., Donati C., Cappa S. F., and Fazio F. (2001) “Syntax and the brain: disentangling grammar by selective anomalies”, NeuroImage (Orlando Fla., Print), published by Academic Press, Orlando, FL, Stati Uniti d'America, vol. 13, pp. 110-118.
599
Pasini A., Pelino V., and Potestà S. (2001) “A neural network model for visibility nowcasting from surface observations: results and sensitivity to physical input variables”, Journal of Geophysical Research. Atmospheres (Online), published by Wiley; [poi] American Geophysical Union, Hoboken, N. J., Stati Uniti d'America, vol. 106, pp. 14951-14959.
600
Rizzo R. (2001) “Self-Organizing Neural Networks Applications for Information Organization”.
601
Tagliaferri R., Pelosi N., Ciaramella A., Longo G., Milano M., and Barone F. (2001) “Soft computing methodologies for spectral analysis”, Computers & geosciences, published by Pergamon Press., New York, Regno Unito, vol. 27, pp. 535-548.
View DOI resources602
Babiloni F., Carducci F., Cerutti S., Liberati D., Rossini P., Urbano A., and Babiloni C. (2000) “Comparison between human and artificial neural network detection of Laplacian-derived electroencephalographic activity related to unilateral voluntary movements”, Computers and biomedical research (Print), published by Academic Press., San Diego [etc. ], Stati Uniti d'America, vol. 33, pp. 59-74.
View DOI resources603
Baccigalupi C., Bedini L., Burigana C., De Zotti G., Farusi A., Maino D., Maris M., Perrotta F., Salerno E., Toffolatti L., and Tonazzini A. (2000) “Neural networks and the separation of cosmic microwave background and astrophysical signals in sky maps”, Monthly notices of the Royal Astronomical Society (Print), published by Blackwell Scientific Publications, Oxford, Regno Unito, vol. 318, pp. 769-780.
604
Calabretta R., Nolfi S., Parisi D., and Wagner G. (2000) “An artificial life model for investigating the evolution of modularity”, Understanding Complex Systems, published by Springer Verlag, Berlin, Germania, pp. 103-113.
View web resources605
Cirrincione M. and Pucci M. (2000) “A Rotor-Flux-Oriented Vector Control of an AC Drive with an Induction Motor using the Progressive Learning Neural Network”, Electrical engineering research report, published by Università di Napoli Federico II., Napoli, Italia, vol. 9.
View DOI resources606
Distante C., Siciliano P., and Vasanelli L. (2000) “Odor discrimination using adaptive resonance theory”, Sensors and actuators. B, Chemical (Print), published by Elsevier Sequoia, Lausanne, Svizzera, vol. 69, pp. 248-252.
607
Lanza C. and Pardelli G. (2000) “Una soggettazione automatica di letteratura grigia con algoritmi di rete neurale artificiale. Due esperimenti ICAS e ILC”, ISTISAN congressi, ISSN 0393-5620, published by Istituto superiore di sanità, Roma (Italia), vol. 67, pp. 52-56.
Books
608
Scafati F. T., Lavorgna M., Mancaruso E., and Vaglieco B. M. (2018) “Nonlinear Systems and Circuits in Internal Combustion Engines-Modeling and Control”, ISBN 978-3-319-67140-6, published by Springer International Publishing, Switzerland, CHE.
609
De Marsico M., Di Baja G. S., and Fred A. (2017) “ICPRAM 2017-Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods”, ISBN 978-989-758-222-6.
View web resources610
De Marsico M., Di Baja G. S., and Fred A. (2016) “ICPRAM 2016-Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods”, ISBN 978-989-758-173-1.
611
Di Maio V. (2016) “2016 International Joint Conference on Neural Networks (IJCNN) Referee primo articolo”.
612
Di Maio V. (2016) “Cognitive Neurodynamics (referee)”.
613
Di Maio V. (2016) “International Joint Conference on Neural Networks (IJCNN) Referee quarto articolo”.
614
Di Maio V. (2016) “International Joint Conference on Neural Networks (IJCNN) Referee secondo articolo”.
615
Di Maio V. (2016) “International Joint Conference on Neural Networks (IJCNN) Referee terzo articolo”.
616
D'Acunto M. (2015) “Nature-inspired computation”, ISBN 978-1-63482-476-7, published by Nova Science Publisher Inc, New York, USA.
View DOI resources617
Baldassarre G. and Mirolli M. (2013) “Computational and Robotic Models of the Hierarchical Organisation of Behaviour”, ISBN 978-3-642-39874-2.
View web resources618
Cirrincione M., Pucci M., and Vitale G. (2012) “Power Converters and AC Electrical Drives with Linear Neural Networks”, ISBN 978-1-4398-1814-5, published by CRC Press, Boca Raton, USA.
View web resources619
Scanzio S. (2012) “Speeding-up Artificial Neural Networks: A Speech Recognition example”, ISBN 978-3-659-20482-1, published by Lambert Academic Publishing (LAP), Saarbrucken, DEU.
620
Barcaro U. (2010) “The interwoven sources of dreams”, ISBN 9781855756267, published by Karnac Books, London, GBR.
621
Dalla Marta A., De Vincenzi M., and Orlandini S. (2002) “Application of artificial neural networks for leaf wetness duration estimation”.
622
Blonda P., Baraldi A., D?addabbo A., Tarantino C., and De Blasi R. (2001) “RBF networks exploiting supervised data in the adaptation of hidden neuron parameters”.
Book chapters
View web resourcesView DOI resources623
Rundo L., Han C., Zhang J., Hataya R., Nagano Y., Militello C., Ferretti C., Nobile M. S., Tangherloni A., Gilardi M. C., Vitabile S., Nakayama H., and Mauri G. (2020) “CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study”, Esposito A., Morabito M. F. F. C., and Pasero E. (eds.), published by Springer Nature Switzerland, Basel, CHE.
624
Liberati D. (2019) “In Silico Drug Design”.
View web resourcesView DOI resources625
Luccioli S., Barzilai A., Ben Jacob E., Bonifazi P., and Torcini A. (2019) “Functional Cliques in Developmentally Correlated Neural Networks”.
View web resourcesView DOI resources626
Shah S., Nawaz W., Jalil B., and Khan H. A. (2019) “Classification of normal and leukemic blast cells in B-ALL cancer using a combination of convolutional and recurrent neural networks”, ISBN 978-981-15-0797-7, Gupta A. and Gupta R. (eds.).
View DOI resources627
Urso A., Fiannaca A., La Rosa M., Ravì V., and Rizzo R. (2019) “Data Mining: Classification and Prediction”, ISBN 978-0-12-811432-2, Guenther R. and Steel D. (eds.), published by Elsevier, Oxford, GBR.
View DOI resources628
Brancati N., Frucci M., Gragnaniello D., and Riccio D. (2018) “Retinal Vessels Segmentation based on a Convolutional Neural Network”, Mendoza M. and Velastín S. (eds.), published by Springer, Cham, Heidelberg, New York, Dordrecht, London, CHE.
View web resourcesView DOI resources629
Brancati N., Frucci M., and Riccio D. (2018) “Multi-classification of breast cancer histology images by using a fine-tuning strategy”, Campilho A., Karray F., and T. H. R. B. (eds.).
View web resourcesView DOI resources630
Guarascio M., Manco G., and Ritacco E. (2018) “Deep Learning”, ISBN 978-0-12-809633-8, Ranganathan S., Nakai K., Gribskov M., and Schönbach C. (eds.).
View web resourcesView DOI resources631
Guarascio M., Ritacco E., Biondo D., Mammoliti R., and Toma A. (2018) “Integrating a framework for discovering alternative app stores in a mobile app monitoring platform”, ISBN 9783319786797.
632
Liberati D. (2018) “COMBINED NATURAL AND ARTIFICIAL NEURAL NETWORK LEARNING IN PROSTHESIS CONTROL”.
633
Oro E., Ruffolo M., and Fermé E. (2018) “Artificial Intelligence for Question Answering-ADBIS Workshop”.
View web resourcesView DOI resources634
Pirrelli V. (2018) “Morphological Theory And Computational Linguistics”, The Oxford Handbook of Morphological Theory, ISBN 978-0-19-966898-4, Audring J. and Masini F. (eds.), published by Oxford University Press, Oxford (Regno Unito), pp. 573-593.
635
Rodriguez I., Manfre' A., Vella F., Infantino I., and Lazkano E. (2018) “Talking with Sentiment: Adaptive Expression Generation Behavior for Social Robots”, F. P. R., G. O. '., S. L. M., I. M. J., and L. E. A. (eds.).
View DOI resources636
Caviglione L., Gaggero M., Lalande J., and Mazurczyk W. (2017) “Understanding information hiding to secure communications and to prevent exfiltration of mobile data”, ISBN 978-0-12-804603-6, Migliardi M., Merlo A., and Baddar S. A. (eds.), published by Academic Press, London, GBR.
View web resourcesView DOI resources637
Cicirelli G. and D'Orazio T. (2017) “Gesture Recognition by Using Depth Data: Comparison of Different Methodologies”, ISBN 978-953-51-3377-3.
638
Liberati D. (2017) “Musicotherapy: Is rhythm able to inhibit inhibitors?”.
639
Liberati D., Paoli" G., Corvó R., Bellazzi R., and Muselli M. (2017) “Automatic rule generation techniques supplement conventional statistics in identifying prognostic factors for head and neck cancer”.
640
Ielpo P., Uricchio V. F., and Pappagallo G. (2016) “Metodi statistici multivariati applicati a data set di acque sotterranee e suoli: source apportionment e classificazione”, ISBN 978-88-6611-516-8.
View web resourcesView DOI resources641
Rizzo R., Fiannaca A., La Rosa M., and Urso A. (2016) “A deep learning approach to DNA sequence classification”, ISBN 978-3-319-44331-7, published by Springer International Publishing, Switzerland, CHE.
View web resourcesView DOI resources642
Rosa J. L. G. (2016) “Neural Networks Applications for the Remote Sensing of Hydrological parameters”, ISBN 978-953-51-2704-8, published by InTech Open Science/Open Minds, Rijeka, HRV.
View web resourcesView DOI resources643
Scano A., Caimmi M., Chiavenna A., Malosio M., and Tosatti L. M. (2016) “A Kinect-Based Biomechanical Assessment of Neurological Patients' Motor Performances for Domestic Rehabilitation”, Hu F., Lu J., and Zhang T. (eds.), published by IGI Global, Hershey, USA.
View web resourcesView DOI resources644
De Gregorio M. and Giordano M. (2015) “Background modeling by weightless neural networks”, ISBN 9783319232218, Murino V., Puppo E., Sona D., Cristani M., and Sansone C. (eds.), published by Springer, Berlin Heidelberg, DEU.
View DOI resources645
De Gregorio M. and Giordano M. (2015) “Exploiting "mental" images in artificial neural network computation”, ISBN 978-3-319-23496-0, Zazzu V., Ferraro M. B., and Guarracino M. R. (eds.), published by Springer, Berlin, DEU.
View web resourcesView DOI resources646
La Rosa M., Fiannaca A., Rizzo R., and Urso A. (2015) “DNA Barcode classification using General Regression Neural Network with different distance models”, ISBN 978-3-319-23496-0, published by Springer International Publishing AG, Berlin, DEU.
View web resourcesView DOI resources647
Rizzo R., Fiannaca A., La Rosa M., and Urso A. (2015) “The General Regression Neural Network to Classify Barcode and mini-barcode DNA”, ISBN 978-3-319-24461-7, Di Serio C., Liò P., Nonis A., and Tagliaferri R. (eds.), published by Springer International Publishing AG, Berlin, DEU.
View web resourcesView DOI resources648
Secci R., Foddis M. L., Mazzella A., Montisci A., and Uras G. (2015) “Artificial Neural Networks and Kriging Method for Slope Geomechanical Characterization”, ISBN 978-3-319-09056-6, published by Springer International Publishing, New York, USA.
View web resourcesView DOI resources649
Bizon K., Continillo G., Lombardi S., Mancaruso E., and Vaglieco B. M. (2014) “ANN-based virtual sensor for on-line prediction of in-cylinder pressure in a diesel engine”, ISBN 978-0-444-63434-4, Klemes J. J., Varbanov P. S., and Liew P. Y. (eds.), published by Elsevier B. V., Amsterdam, BEL.
650
Casagranda I., Costantino G., Falavigna G., Furlan R., and Ippoliti R. (2014) “Artificial Neural Networks and risk stratification in Emergency department”.
View DOI resources651
Gaggero M., Gnecco G., and Sanguineti M. (2014) “Suboptimal policies for stochastic N-stage optimization problems: accuracy analysis and a case study from optimal consumption”, published by Springer-Verlag, Berlin Heidelberg, DEU.
View web resourcesView DOI resources652
Tonacci A., Corda D., Tartarisco G., Pioggia G., and Domenici C. (2014) “A smart system to detect volatile organic compounds produced by hydrocarbons on seawater”, Sensors and Microsystems, ISBN 978-3-319-00683-3, published by Springer International Publishing, CH-6330 Cham (ZG) (Svizzera), vol. 268 LNEE, pp. 99-102.
View web resourcesView DOI resources653
Bacciu D., Chessa S., Gallicchio C., Micheli A., and Barsocchi P. (2013) “An experimental evaluation of reservoir computation for ambient assisted living”, ISBN 978-3-642-35466-3, Apolloni B., Bassis S., Esposito A., and Morabito F. C. (eds.), published by Springer, Heidelberg, DEU.
View web resourcesView DOI resources654
Cantoni V., Ferone A., Petrosino A., and Sanniti D. B. G. (2013) “A Supervised Approach to 3D Structural Classification of Proteins”, ISBN 978-3-642-41189-2, Petrosino A., Maddalena L., and Pala P. (eds.), published by Springer-Verlag, Berlin, DEU.
View DOI resources655
Cardoso D., De Gregorio M., Lima P., João G., and Felipe F. (2012) “A Weightless Neural Network-Based Approach for Stream Data Clustering”.
View web resourcesView DOI resources656
Gallicchio C., Micheli A., Barsocchi P., and Chessa S. (2012) “User movements forecasting by reservoir computing using signal streams produced by mote-class sensors”, ISBN 978-3-642-29478-5, Del Ser J., Jorswieck E. A., Miguez J., Matinmikko M., Palomar D. P., Sanz S. S., and Gil Lopez S. (eds.), published by Springer, London, GBR.
View web resources657
Maddalena L. and Petrosino A. (2012) “Neural Networks in Video Surveillance: A Perspective View”, ISBN 9781439856840, Pal S. K., Petrosino A., and Maddalena L. (eds.), published by CRC Press, Boca Raton, USA.
View DOI resources658
Maniscalco U. and Pilato G. (2012) “Multi Soft-Sensors Data Fusion In Spatial Forecasting Of Environmental Parameters”, ISBN 978-981-4397-94-0.
659
Bilotta E., Cerasa A., Pantano P., Quattrone A., Staino A., and Stramandinoli F. (2011) “Evolving Cellular Neural Networks for the Automated Segmentation of Multiple Sclerosis Lesions”.
View web resources660
Pezzulo G. and Butz M. V. (2011) “Schema-based architectures of machine learning”, Encyclopedia of the Sciences of Learning, Seel N. M. (ed.), published by Springer, Dordrecht (Paesi Bassi), pp. 2942-2945.
View web resourcesView DOI resources661
Borghi A. M., Caligiore D., and Scorolli C. (2010) “Objects, words and actions: Some reasons why embodied models are badly needed in cognitive psychology”.
662
Calabretta R. (2010) “Evolution, (sequential) learning and generalization in modular and nonmodular visual neural networks”, published by Cambridge University Press, Cambridge, GBR.
View web resources663
Looi J. C. L., Pagani M., Nardo D., Raphael B., and Wahlund L. (2010) “Structural and functional neuroimaging in PTSD: A neurobiological update”, Sher L. and Vilens A. (eds.), published by Nova Science Publishers, New York, USA.
View DOI resources664
Alessandri A., Cervellera C., Cuneo M., and Gaggero M. (2009) “Nonlinear model predictive control for resource allocation in the management of intermodal container terminals”, published by Springer-Verlag, Berlin Heidelberg, DEU.
665
Calabretta R. (2009) “Evolution, (sequential) learning and generalization in modular and nonmodular visual neural networks”, published by Cambridge University Press, Cambridge, GBR.
View DOI resources666
D'Orazio T., Leo M., and Guaragnella C. (2009) “Neural Network Approaches for Defect Detection in Composite Materials”, ISBN 978-1-4200-9332-2, published by Taylor & Francis Ltd., Abingdon, GBR.
View DOI resources667
Ferrari E. and Muselli M. (2009) “Efficient constructive techniques for training Switching Neural Networks”, ISBN 978-3-642-04511-0, Franco L., Elizondo D. A., and Jerez J. M. (eds.), published by Springer-Verlag, Berlin, DEU.
668
Pasini A. (2009) “Neural network modeling in climate change studies”, ISBN 978-1-4020-9117-9, Haupt S. E., Pasini A., and Marzban C. (eds.), published by Springer, New York, USA.
669
Pasini A. (2009) “Neural networks for characterization and forecasting in the boundary layer via Radon data”, ISBN 978-1-4020-9117-9, Haupt S. E., Pasini A., and Marzban C. (eds.), published by Springer, New York, USA.
View web resourcesView DOI resources670
Tummolini L., Mirolli M., and Castelfranchi C. (2009) “Stigmergic Cues and their Uses in Coordination: An Evolutionary Approach”, ISBN 978-1-4200-7023-1, Weyns D. and Uhrmacher A. M. (eds.), published by CRC Press, Boca Raton, USA.
671
Bajo M., Umgiesser G., Borghesan A., and Zuliani A. (2008) “Post-processing of numerical model output through a neural network”, ISBN 88-89405-07-4, Campostrini P. (ed.), published by Multigraf, Spinea, ITA.
672
Leone A. P., Calabrò G., Coppola E., Maffei C., Menenti M., Tosca M., Vella M., and Buondonno A. (2008) “Prediction of Soil Properties with VIS-NIR-SWIR Reflectance Spectroscopy and Artificial Neural Networks: A Case Study on three Pedoenvironments of the Campania Region, Italy”, ISBN 978-3-923381-56-2, Dazzi C. and Costantini E. (eds.).
View web resourcesView DOI resources673
Colantonio S., Gurevich I. B., and Salvetti O. (2007) “Automatic fuzzy-neural based segmentation of microscopic cell images”, ISBN 978-3-540-76299-7, Perner P. and Salvetti O. (eds.).
View web resources674
Little S., Salvetti O., and Perner P. (2007) “Semi-automatic semantic tagging of 3D images from pancreas cells”, ISBN 978-3-540-76299-7, Perner P. and Salvetti O. (eds.).
675
Mirolli M., Cecconi F., and Parisi D. (2007) “A Neural Network Model for Explaining the Asymmetries between Linguistic Production and Linguistic Comprehension”, published by Lawrence Erlbaum Associates Inc., Mahwah, USA.
View web resourcesView DOI resources676
Schembri M., Mirolli M., and Baldassarre G. (2007) “Evolving internal reinforcers for an intrinsically motivated reinforcement-learning robot”, ISBN 978-1-4244-1116-0, Demiris Y., Scassellati B., and Mareschal D. (eds.), published by Imperial College, London, GBR.
View DOI resources677
Carcano E. C., Muselli M., and Bartolini P. (2006) “Recurrent neural networks in Rainfall-Runoff modeling at daily scale”, Baglio S. and Bulsara A. (eds.).
678
Cecconi F. and Campennì M. (2006) “Recurrent and concurrent neural networks for objects recognition”, published by Acta Press , Anaheim, USA.
View DOI resources679
Cervellera C. and Muselli M. (2006) “Deterministic learning and an application in optimal control”, ISBN 0-12-014782-3, Hawkes P. W. (ed.), published by Academic Press, San Diego, USA.
View web resources680
Zani A. and Proverbio A. M. (2006) “ERP signs of frontal and occipital processing of visual targets and distractors within and without the channel of spatial attention”, ISBN 1-59454-779-3, Dupri J. R. (ed.), published by Nova Science Publishers, Hauppauge, USA.
View DOI resources681
Aiello G., Gaglio S., Lo Re G., Storniolo P., and Urso A. (2005) “The Random Neural Network Model for the On-line Multicast Problem”, ISBN 978-1-4020-3431-2, Apolloni B., Marinaro M., and Tagliaferri R. (eds.).
682
Calabretta, R., Parisi, and D. (2005) “Evolutionary Connectionism and Mind/Brain Modularity”, published by MIT Press, Cambridge [MA], USA.
683
Dalla Marta A., De Vincenzi M., and Orlandini S. (2005) “Application of artificial neural networks for leaf wetness duration estimation”, Maracchi G., Bogatai L. K., Orlandini S., Dalla Marta A., and Rossi F. (eds.).
684
Mirolli M. and Parisi D. (2005) “Language as an aid to categorization: A neural network model of early language acquisition”, published by World Scientific Publ. Co., Singapore, SGP.
685
Wagner, G. P., Mezey, J., Calabretta, and R. (2005) “Natural Selection and the origin of modules”, published by MIT Press, Cambridge [MA], USA.
686
Holden R. and Cangelosi A. (2004) “Limits to locality: Cellular Automata v Pulsed Neural Networks”.
687
Riga T., Cangelosi A., and Greco A. (2004) “Symbol grounding transfer with hybrid self-organizing/supervised neural networks”.
688
Alessandri A., Coletta P., and Parisini T. (2003) “Model-based fault detection in a high-pressure heater line”.
689
Baldassarre G. (2003) “Forward and bidirectional planning based on reinforcement learning and neural networks in a simulated robot”, published by Springer-Verlag, Berlin, DEU.
690
Colagrossi A., Sciarrone F., and Seccaroni C. (2003) “Using neural networks to automate the classification of works of art”.
691
Guðrún ÓL., Di Natale C., and Macagnano A. (2003) “Measurements of quality of cod by electronic noses”, ISBN 9076998140, published by Wageningen Academic Publishers, Wageningen, NLD.
692
Nardin A., Schrefler B., and Lefik M. (2003) “Application of artificial neural network for identification of parameters of a constitutive law for soils”.
693
Baldassarre G. (2002) “A biologically plausible model of human planning based on neural networks and Dyna-PI models”.
694
Brivio P. A., Binaghi E., Gallo I., and Maggi M. (2002) “Contextual multitemporal classification of burned areas in coarse resolution imagery”, ISBN 81-7736-132-5, Binaghi E., Brivio P. A., and Serpico S. B. (eds.), published by Research Signpost, Trivandrum, IND.
695
Morgavi G. and Morando M. (2002) “A neural network hybrid model for an optical braille recognitor”, Mastorakis N. E., Mladenov V., and Bojkovic Z. (eds.), published by World Scientific and Engineering Academy and Society (WSEAS), Athens, GRC.
696
Nolfi S. (2002) “Learning and Evolution in Neural Networks”, published by MIT Press, Cambridge [MA], USA.
697
Nolfi S. and Parisi D. (2002) “Evolution of Artificial Neural Networks”, published by MIT Press, Cambridge [MA], USA.
Edited volumes
View web resources698
Marzi C. and Pirrelli V. (eds.) (2016) “Word knowledge and word usage: A Foreword”, Rivista di Linguistica, ISSN 1120-2726, published by Pacini, Ospedaletto (Italia), vol. 28. 1, pp. 3-6.
View web resourcesView DOI resources699
Marzi C. and Pirrelli V. (eds.) (2016) “Word knowledge and word usage: A foreword”, Lingue e linguaggio, ISSN 1720-9331, ISBN 978-88-15-26226-4, published by Il Mulino, Bologna (Italia), vol. XV. 1, pp. 3-6.
Conference papers
View web resources700
Rorberi S. and Marzi C. (2019) “Modelling the interaction of regularity and morphological structure: the case of Russian verb inflection”, International Symposium of Morphology (ISMo) 2019, Université de Paris, France, 25-27/09/2019, Crysmann B. and Villoing F. (eds.), vol. 2019, pp. 107-110.
View web resources701
Marzi C., Ferro M., Nahli O., Belik P., Bompolas S., and Pirrelli V. (2018) “Evaluating Inflectional Complexity Crosslinguistically: a Processing Perspective”, Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), ISBN 979-10-95546-00-9, Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan, 7-12/05/2018, Calzolari N., Choukri K., Cieri C., Declerck T., Goggi S., Hasida K., Isahara H., Maegaard B., Mariani J., Mazo H., Moreno A., Odijk J., Piperidis S., and Tokunaga T. (eds.), published by European language resources association (ELRA), Paris (Francia), vol. 2018, pp. 3860-3866.
702
D'Andrea E., Di Francesco F., Dini V., Lazzerini B., Romanelli M., and Salvo P. (2017) “Physical activity recognition from sub-bandage sensors using both feature selection and extraction”, ISBN 9782875870391, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges (Belgium), 26-28/04/2017, pp. 141-146.
View web resources703
Del Vigna F., Petrocchi M., Tesconi M., Cimino A., and Dell'Orletta F. (2017) “Hate me, hate me not: Hate speech detection on Facebook”, CEUR workshop proceedings, ISSN 1613-0073, ITA-SEC 17, Venezia, Italia, 17-20/01/2017, published by M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen, Aachen (Germania), vol. 1816, pp. 86-95.
View web resources704
Pirrelli V. (2017) “Co-activation and competition effects in lexical storage and processing”, 4th Patras International Conference of Graduate Students in Linguistics, Patras, Greece, 20-22/05/ 2016, pp. 1-21.
705
Vadicamo L., Carrara F., Falchi F., Cimino A., Dell'Orletta F., Cresci S., and Tesconi M. (2017) “Cross-media learning for image sentiment analysis in the wild”, ICCV 2017 IEEE International Conference on Computer Vision Workshops, Venezia, Italy, 22-29 October 2017, 10 pages.
View web resources706
Gallicchio C., Micheli A., Pedrelli L., Vozzi F., and Parodi O. (2015) “Preliminary experimental analysis of Reservoir Computing approach for balance assessment”, CEUR workshop proceedings, ISSN 1613-0073, 1st International Workshop on Advanced Analytics and Learning on Temporal Data AALTD 2015, 11/09/2015, published by M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen, Aachen (Germania), vol. 1425, pp. 57-62.
View web resources707
Ferro M., Marzi C., and Pirrelli V. (2011) “T2HSOM: Understanding the Lexicon by Simulating Memory Processes for Serial Order”, First International Workshop on Lexical Resources, First International Workshop on Lexical Resources, Ljubljana Slovenia, 1-5 Agosto 2011, Sagot B. (ed.), pp. 32-41.
View DOI resources708
Gigliotta O., Pezzulo G., and Nolfi S. (2010) “Emergence of an internal model in evolving robots subjected to sensory deprivation”, Lecture notes in computer science, ISSN 0302-9743, ISBN 978-3-642-15193-4, 11th International Conference on Simulation of Adaptive Behavior, SAB 2010, Paris, August 25-28, 2010, published by Springer-Berlin (Germania), vol. 6226, pp. 575-586.
View DOI resources709
Landi A., Piaggi P., and Pioggia G. (2009) “Backpropagation-Based Non Linear PCA for Biomedical Applications”, Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on, ISBN 978-1-4244-4735-0, Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on, Pisa, Italy, 30 Nov-02 Dec, pp. 635-640.
710
Coppini G., Paterni M., Guerriero L., and Ferdeghini E. M. (2008) “Segmentation of lung fields in digital chest radiographs by artificial neural networks”, Primo Congresso GNB (Pisa, 3-7 luglio 2008). Atti, ISBN 8855529838, Primo Congresso Nazionale GNB, Pisa, 3-5 luglio 2008, Burattini, Contro, Dario, and Landini (eds.), published by Pàtron Editore, Bologna (Italia), pp. 645-646.
View web resources711
Cantini F., Emdin M., Passino C. S., Varanini M., and Conforti F. (2003) “Validation of a novel algorithm for ventricular repolarization analysis: Use of physionet resources”, Computers in cardiology, ISSN 0276-6574, IEEE Computers in Cardiology 2003, Tessoniki, Grecia, 2003, published by IEEE Computer Society, Long Beach, Calif (Stati Uniti d'America), vol. 30, pp. 509-512.
712
Lanza C. and Pardelli G. (2000) “Una soggettazione automatica di letteratura grigia con algoritmi di rete neurale artificiale. Due esperimenti ICAS e ILC”, ISTISAN congressi, ISSN 0393-5620, La letteratura grigia: politica e pratica. 3 Convegno Nazionale, Roma, 25-26 novembre 1999, Alberani V. and De Castro P. (eds.), published by Istituto superiore di sanità, Roma (Italia), vol. 67, pp. 52-56.
Conference contributions
View web resourcesView DOI resources713
Abbatangelo M., Carmona E. N., and Sberveglieri V. (2020) “How Nanotechnology Can Help the "Zero Hunger" Goal?”, ECS meeting, 10/05/2020, 13/05/2020.
View web resourcesView DOI resources714
Carrara F., Amato G., Falchi F., and Gennaro C. (2020) “Continuous ODE-defined image features for adaptive retrieval”, ISBN 978-1-4503-7087-5, ICMR '20-International Conference on Multimedia Retrieval, Dublin, Ireland, 8-11 June, 2020, pp. 198-206.
View web resourcesView DOI resources715
Floridia M., Laganà D., Mastroianni C., Meo M., and Renga D. (2020) “Load Management with Predictions of Solar Energy Production for Cloud Data Centers”, ISBN 978-1-5090-6631-5, ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, May 2020, published by IEEE, New York, USA.
View web resourcesView DOI resources716
Naeem M., Paragiola G., Coronato A., and De Pietro G. (2020) “A CNN Based Monitoring System to Minimize Medication Errors during Treatment Process at Home”, ISBN 9781450376303, International Conference on Applications of Intelligent Systems (APPIS 2020), Las Palmas de Gran Canaria Spain, 7/01/2020, 9/01/2020.
717
Amato G., Bolettieri P., Carrara F., Ciampi L., Gennaro C., Leone G. R., Moroni D., Pieri G., and Vairo C. (2019) “Parking Lot Monitoring with Smart Cameras”, 5th Italian Conference on ICT for Smart Cities And Communities, Pisa, Italy, 18-20 September, 2019, pp. 1-3.
View web resourcesView DOI resources718
Amato G., Bolettieri P., Carrara F., Debole F., Falchi F., Gennaro C., Vadicamo L., and Vairo C. (2019) “VISIONE at VBS2019”, ISBN 978-3-030-05716-9, MMM 2019-25th International Conference on Multimedia Modeling, Thessaloniki, Greece, 08-11/01/2019, published by Springer International Publishing, CH-6330 Cham (ZG), CHE, pp. 591-596.
View web resourcesView DOI resources719
Amato G., Carrara F., Falchi F., Gennaro C., and Lagani G. (2019) “Hebbian learning meets deep convolutional neural networks”, ISBN 9783030306410, Image Analysis and Processing-ICIAP 2019, Trento, Italia, 9/9/2019, 13/9/2019, published by Springer, Berlin, DEU, pp. 324-334.
View web resourcesView DOI resources720
Amato G., Ciampi L., Falchi F., and Gennaro C. (2019) “Counting vehicles with deep learning in onboard UAV imagery”, ISBN 978-1-7281-2999-0, ISCC 2019-IEEE Symposium on Computers and Communications, Barcelona, Spain, 30 June 2019-03 July 2019, pp. 1-6.
View web resourcesView DOI resources721
Amato G., Ciampi L., Falchi F., Gennaro C., and Messina N. (2019) “Learning pedestrian detection from virtual worlds”, ISBN 9783030306410, Image Analysis and Processing-ICIAP 2019, Trento, Italia, 9/9/2019, 13/9/2019, published by Springer, Berlin, DEU, pp. 302-312.
View DOI resources722
Amato G., Falchi F., Gennaro C., Massoli F. V., Passalis N., Tefas A., Trivilini A., and Vairo C. (2019) “Face Verification and Recognition for Digital Forensics and Information Security”, ISBN 978-1-7281-2827-6, 7th International Symposium on Digital Forensics and Security (ISDFS 2019), Barcelos, Portugal, 10/6/2019, 12/6/2019.
723
Amura A., Tonazzini A., Salerno E., Pagnotta S., and Palleschi V. (2019) “Color segmentation algorithms to support automatism of graphic documentation in restoration”, XV Conferenza del Colore, Macerata, Italy, 5-7 September, 2019.
724
Bianco I., Russo T., Viaggiu E., Sarno D., Caroppo C., and Congestri R. (2019) “Marine phytoplankton database of Latium coastal waters (Middle Tyrrhenian Sea-Italy): checklist and Self Organizing Maps analyses of data collected from 2002 to 2017”, Riunione Scientifica del Gruppo di Lavoro per la Algologia, Societa Italiana di Botanica, Bari, 15-16 novembre 2019, pp. 11-11.
View web resourcesView DOI resources725
Bolettieri P., Carrara F., Debole F., Falchi F., Gennaro C., Vadicamo L., and Vairo C. (2019) “An Image Retrieval System for Video”, International Conference on Similarity Search and Applications (SISAP), Newark, NJ, USA, 2-4/10/2019, pp. 332-339.
View DOI resources726
Brusaferri A., Matteucci M., Portolani P., and Spinelli S. (2019) “Nonlinear system identification using a recurrent network in a Bayesian framework”, ISBN 978-1-7281-2927-3, Industrial Informatics (INDIN), 23/07/2019-25/07/2019, published by IEEE, New York, USA, pp. 319-324.
View web resourcesView DOI resources727
Caldelli R., Becarelli R., Carrara F., Falchi F., and Amato G. (2019) “Exploiting CNN layer activations to improve adversarial image classification”, ISBN 978-1-5386-6249-6, ICIP 2019-IEEE International Conference on Image Processing, Taipei, Taiwan, 22-25 September, 2019, published by Institute of Electrical and Electronic Engineers;, Red Hook, NY, Stati Uniti d'America, pp. 2289-2293.
View web resourcesView DOI resources728
Carrara F., Amato G., Falchi F., and Gennaro C. (2019) “Evaluation of continuous image features learned by ODE nets”, ISBN 9783030306410, Image Analysis and Processing-ICIAP 2019, Trento, Italia, 9/9/2019-13/9/2019, published by Springer, Berlin, DEU, pp. 432-442.
View web resourcesView DOI resources729
Carrara F., Becarelli R., Caldelli R., Falchi F., and Amato G. (2019) “Adversarial Examples Detection in Features Distance Spaces”, ISBN 978-3-030-11012-3, ECCV: European Conference on Computer Vision, Monaco, Germania, 8-14 Settembre 2018, published by Springer, Cham, Heidelberg, New York, Dordrecht, London, CHE, pp. 313-327.
View web resourcesView DOI resources730
Carrara F., Caldelli R., Falchi F., and Amato G. (2019) “On the robustness to adversarial examples of neural ODE image classifiers”, ISBN 978-1-7281-3217-4, WIFS 2019-IEEE International Workshop on Information Forensics and Security, Delft, Netherlands, 9-12 December 2019.
731
Cicirelli G., Marani R., Petitti A., Annalisa M., D'Orazio T., and Impedovo D. (2019) “An integrated system of low-cost cameras for monitoring neuro-degenerative diseases”, Prima Conferenza Nazionale di Robotica e Macchine Intelligenti (I-RIM 2019), Roma, 18-20 Ottobre 2019.
View web resourcesView DOI resources732
Coro G., Masetti G., Bonhoeffer P., and Betcher M. (2019) “Distinguishing Violinists and Pianists Based on Their Brain Signals”, ISBN 978-3-030-30487-4, ICANN 2019: Theoretical Neural Computation 28th International Conference on Artificial Neural Networks, Monaco di Baviera, 17-19/10/2019, published by Springer, Cham, Heidelberg, New York, Dordrecht, London, CHE, pp. 123-137.
View web resourcesView DOI resources733
De Bonis M., Amato G., Falchi F., Gennaro C., and Manghi P. (2019) “Deep learning techniques for visual food recognition on a mobile app”, ISBN 978-3-319-98678-4, 11th International Conference on Multimedia and Network Information Systems, MISSI 2018, Wroclaw; Poland, 12-14 September 2018, pp. 303-312.
734
De Logu F., Ugolini F., Simi S., Maio V., Nassini R., Vezzosi S., Massi D., and Laurino M. (2019) “Automatic detection of histopathological melanoma images using an Artificial Intelligence algorithm”, 6th Digital Pathology & AI Congress, London, UK, December 05-06, 2019.
View web resourcesView DOI resources735
Di Benedetto M., Meloni E., Amato G., Falchi F., and Gennaro C. (2019) “Learning Safety Equipment Detection using Virtual Worlds”, ISBN 9781728146737, 2019 International Conference on Content-Based Multimedia Indexing (CBMI), Dublin, Ireland, 4/9/2019, 6/9/2019, published by IEEE, Piscataway, Stati Uniti d'America.
736
Folino F., Folino G., Guarascio M., and Pontieri L. (2019) “Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data”, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Portland, Oregon, USA, 4-6/11/2019.
View DOI resources737
Gargiulo F., Silvestri S., and Ciampi M. (2019) “Exploit Hierarchical Label Knowledge for Deep Learning”, IEEE Special Track on Artificial Intelligence for Healthcare: from black box to explainable models (AI4H: B2E 2019) in conjunction with 32nd IEEE CBMS International Symposium on Computer-Based Medical Systems (IEEE CBMS 2019), Córdoba, Spain, 05-07/07/2019, pp. 539-542.
View web resources738
Giordano M. and De Gregorio M. (2019) “An evolutionary approach for optimizing weightless neural networks”, ISBN 9782875870650, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019, Bruges, Belgium, 24-26/04/2019, pp. 325-330.
View web resources739
Kianoush S., Savazzi S., and Rampa V. (2019) “PASSIVE DETECTION AND DISCRIMINATION OF BODY MOVEMENTS IN THE SUB-THZ BAND: A CASE STUDY”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2019), Brighton, UK, May 2019.
View web resources740
Kianoush S., Savazzi S., and Rampa V. (2019) “PASSIVE DETECTION AND DISCRIMINATION OF BODY MOVEMENTS IN THE SUB-THZ BAND: A CASE STUDY”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, 12-17 May 2019, published by IEEE Service Center, Piscataway, NJ, Stati Uniti d'America, pp. 1597-1601.
741
La Cascia M., Infantino I., and Vella F. (2019) “Recognition of Human Actions Through Deep Neural Networks for Multimedia Systems Interaction”, Eleventh International Conference on Advances in Multimedia MMEDIA 2019, 24-28/93/2019.
View DOI resources742
La Tona G., Luna M., Di Piazza A., and Di Piazza M. C. (2019) “Development of a Forecasting Module based on Tensorflow for use in Energy Management Systems”, ISBN 978-1-7281-4878-6, 45th Annual Conference of the IEEE Industrial Electronics Society (IES), IECON 2019, Lisbon, Portugal, 14-17 ottobre 2019, published by IEEE Operations Center, Piscataway, NJ, Stati Uniti d'America, pp. 2911-2916.
View web resourcesView DOI resources743
Lucchese C., Nardini F. M., Pasumarthi R. K., Bruch S., Bendersky M., Wang X., Oosterhuis H., Jagerman R., and De Rijke M. (2019) “Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning”, ISBN 978-1-4503-6172-9, 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Parigi, Francia, 21/07/2019, 25/07/2019, pp. 1419-1420.
744
Manco G., Folino F., Pontieri L., and Ritacco E. (2019) “Generative Adversarial Networks for Temporally-Marked Event Sequences”, 8th Italian Workshop on Machine Learning and Data Mining, Rende (CS), 19/11/2019.
745
Marani R., Milella A., Petitti A., and Reina G. (2019) “Deep learning based image segmentation for grape bunch detection”, The 12th European Conference on Precision Agriculture, Montpellier, France, 8-11 July 2019.
View web resourcesView DOI resources746
Massoli F. V., Amato G., Falchi F., Gennaro C., and Vairo C. (2019) “Improving Multi-scale Face Recognition Using VGGFace2”, ISBN 9783030307530, BioFor Workshop on Recent Advances in Digital Security: Biometrics and Forensics, Trento, Berlino, 8/9/2019, published by Springer, Berlin, DEU, pp. 21-29.
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