| A new design methodology to predict wind farm energy production by means of a spiking neural network–based system S Brusca, G Capizzi, G Lo Sciuto, G Susi International Journal of Numerical Modelling: Electronic Networks, Devices …, 2019 | 45 | 2019 |
| Hardware design of LIF with Latency neuron model with memristive STDP synapses S Acciarito, GC Cardarilli, A Cristini, L Di Nunzio, R Fazzolari, GM Khanal, ... Integration 59, 81-89, 2017 | 38 | 2017 |
| A spiking neural network-based long-term prediction system for biogas production G Capizzi, GL Sciuto, C Napoli, M Woźniak, G Susi Neural Networks 129, 271-279, 2020 | 31 | 2020 |
| Spiking neural networks based on LIF with latency: Simulation and synchronization effects GC Cardarilli, A Cristini, L Di Nunzio, M Re, M Salerno, G Susi 2013 Asilomar Conference on Signals, Systems and Computers, 1838-1842, 2013 | 31 | 2013 |
| A spiking neural network-based model for anaerobic digestion process GL Sciuto, G Susi, G Cammarata, G Capizzi 2016 International Symposium on Power Electronics, Electrical Drives …, 2016 | 27 | 2016 |
| Synaptic behaviour in ZnO–rGO composites thin film memristor GM Khanal, S Acciarito, GC Cardarilli, A Chakraborty, LD Nunzio, ... Electronics letters 53 (5), 296-298, 2017 | 22 | 2017 |
| An a VLSI driving circuit for memristor-based STDP S Acciarito, A Cristini, L Di Nunzio, GM Khanal, G Susi 2016 12th Conference on Ph. D. Research in Microelectronics and Electronics …, 2016 | 22 | 2016 |
| Accurate latency characterization for very large asynchronous spiking neural networks M Salerno, G Susi, A Cristini BIOINFORMATICS 2011-Proceedings of the International Conference on …, 2011 | 18 | 2011 |
| Comparison of resampling techniques for imbalanced datasets in machine learning: application to epileptogenic zone localization from interictal intracranial EEG recordings in … G Varotto, G Susi, L Tassi, F Gozzo, S Franceschetti, F Panzica Frontiers in Neuroinformatics 15, 715421, 2021 | 17 | 2021 |
| A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency, and heterosynaptic STDP G Susi, L Antón Toro, L Canuet, ME López, F Maestú, CR Mirasso, ... Frontiers in neuroscience 12, 408479, 2018 | 17 | 2018 |
| A continuous-time spiking neural network paradigm A Cristini, M Salerno, G Susi Advances in Neural Networks: Computational and Theoretical Issues, 49-60, 2015 | 17 | 2015 |
| Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography A Giovannetti, G Susi, P Casti, A Mencattini, S Pusil, ME López, ... Neural Computing and Applications 33 (21), 14651-14667, 2021 | 13 | 2021 |
| Audinect: An aid for the autonomous navigation of visually impaired people based on virtual interface M Salerno, M Re, A Cristini, G Susi, M Bertola, E Daddario, F Capobianco Int. J. Hum. Comput. Interact 4 (1), 25-33, 2013 | 12 | 2013 |
| Path multimodality in a Feedforward SNN module, using LIF with latency model G Susi, A Cristini, M Salerno Neural Network World 26 (4), 363, 2016 | 9 | 2016 |
| Spiking neural networks as continuous-time dynamical systems: fundamentals, elementary structures and simple applications M Salerno, G Susi, A Cristini, Y Sanfelice, A D’Annessa ACEEE INTERNATIONAL JOURNAL ON INFORMATION TECHNOLOGY 3 (1), 80-89, 2013 | 7 | 2013 |
| nMNSD—A Spiking Neuron-Based Classifier That Combines Weight-Adjustment and Delay-Shift G Susi, LF Antón-Toro, F Maestú, E Pereda, C Mirasso Frontiers in Neuroscience 15, 582608, 2021 | 6 | 2021 |
| Healthy and pathological neurocognitive aging: spectral and functional connectivity analyses using magnetoencephalography G Susi, J de Frutos-Lucas, G Niso, SM Ye-Chen, LA Toro, BNC Vilca, ... Oxford Research Encyclopedia of Psychology, 2019 | 6 | 2019 |
| Bio-inspired temporal-decoding network topologies for the accurate recognition of spike patterns G Susi Transactions on Machine Learning and Artificial Intelligence 3 (4), 27, 2015 | 6 | 2015 |
| FNS allows efficient event-driven spiking neural network simulations based on a neuron model supporting spike latency G Susi, P Garcés, E Paracone, A Cristini, M Salerno, F Maestú, E Pereda Scientific reports 11 (1), 12160, 2021 | 5 | 2021 |
| FNS: an event-driven spiking neural network framework for efficient simulations of large-scale brain models G Susi, P Garces, A Cristini, E Paracone, M Salerno, F Maestu, E Pereda arXiv preprint arXiv:1801.00864, 2018 | 4 | 2018 |
Marco ReUniversity of Rome Tor VergataVerified email at uniroma2.it
