| A machine learning approach for detecting cognitive interference based on eye-tracking data A Rizzo, S Ermini, D Zanca, D Bernabini, A Rossi Frontiers in Human Neuroscience 16, 806330, 2022 | 12 | 2022 |
| Neural network training as a dissipative process M Gori, M Maggini, A Rossi Neural Networks 81, 72-80, 2016 | 8 | 2016 |
| Machine Learning at the Edge: a few applicative cases of Novelty Detection on IIoT gateways G Burresi, A Rizzo, M Lorusso, S Ermini, A Rossi, F Cariaggi 2019 8th Mediterranean Conference on Embedded Computing (MECO), 1-4, 2019 | 7 | 2019 |
| Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow F Giannini, V Laveglia, A Rossi, D Zanca, A Zugarini arXiv preprint arXiv:1703.05298, 2017 | 7 | 2017 |
| ATM Protection Using Embedded Deep Learning Solutions A Rossi, A Rizzo, F Montefoschi Artificial Neural Networks in Pattern Recognition: 8th IAPR TC3 Workshop …, 2018 | 2 | 2018 |
| Auto-associative recurrent neural networks and long term dependencies in novelty detection for audio surveillance applications A Rossi, F Montefoschi, A Rizzo, M Diligenti, C Festucci IOP Conference Series: Materials Science and Engineering 261 (1), 012009, 2017 | 2 | 2017 |
| On-line Learning on Temporal Manifolds M Maggini, A Rossi AI* IA 2016 Advances in Artificial Intelligence: XVth International …, 2016 | 2 | 2016 |
| The principle of cognitive action-Preliminary experimental analysis M Gori, M Maggini, A Rossi arXiv preprint arXiv:1701.02377, 2017 | 1 | 2017 |
| Collapsing of dimensionality M Gori, M Maggini, A Rossi arXiv preprint arXiv:1701.00831, 2017 | | 2017 |
Marco MagginiProfessor of Computer Science, University of SienaEmail verificata su unisi.it
