| Self-configuring robot path planning with obstacle avoidance via deep reinforcement learning B Sangiovanni, GP Incremona, M Piastra, A Ferrara IEEE Control Systems Letters 5 (2), 397-402, 2020 | 88 | 2020 |
| Deep reinforcement learning for collision avoidance of robotic manipulators B Sangiovanni, A Rendiniello, GP Incremona, A Ferrara, M Piastra 2018 European Control Conference (ECC), 2063-2068, 2018 | 87 | 2018 |
| Online fall detection using recurrent neural networks M Musci, D De Martini, N Blago, T Facchinetti, M Piastra arXiv preprint arXiv:1804.04976, 2018 | 75 | 2018 |
| Online fall detection using recurrent neural networks on smart wearable devices M Musci, D De Martini, N Blago, T Facchinetti, M Piastra IEEE Transactions on Emerging Topics in Computing 9 (3), 1276-1289, 2020 | 72 | 2020 |
| Embedded real-time fall detection with deep learning on wearable devices E Torti, A Fontanella, M Musci, N Blago, D Pau, F Leporati, M Piastra 2018 21st euromicro conference on digital system design (DSD), 405-412, 2018 | 66 | 2018 |
| Embedding recurrent neural networks in wearable systems for real-time fall detection E Torti, A Fontanella, M Musci, N Blago, D Pau, F Leporati, M Piastra Microprocessors and Microsystems 71, 102895, 2019 | 41 | 2019 |
| Dialogue management in conversational agents through psychology of persuasion and machine learning V Carfora, F Di Massimo, R Rastelli, P Catellani, M Piastra Multimedia Tools and Applications 79 (47), 35949-35971, 2020 | 38 | 2020 |
| Distributed and persistent evolutionary algorithms: a design pattern A Bollini, M Piastra Genetic Programming: Second European Workshop, EuroGP’99 Göteborg, Sweden …, 1999 | 26 | 1999 |
| Self-organizing adaptive map: Autonomous learning of curves and surfaces from point samples M Piastra Neural Networks 41, 96-112, 2013 | 17 | 2013 |
| Phase polarity in a ferrofluid monolayer of shifted-dipole spheres M Piastra, EG Virga Soft Matter 8 (42), 10969-10981, 2012 | 14 | 2012 |
| Deep recurrent neural networks for edge monitoring of personal risk and warning situations E Torti, M Musci, F Guareschi, F Leporati, M Piastra Scientific Programming 2019 (1), 9135196, 2019 | 13 | 2019 |
| Framing and tailoring prefactual messages to reduce red meat consumption: Predicting effects through a psychology-based graphical causal model P Catellani, V Carfora, M Piastra Frontiers in Psychology 13, 825602, 2022 | 12 | 2022 |
| Deep reinforcement learning based self-configuring integral sliding mode control scheme for robot manipulators B Sangiovanni, GP Incremona, A Ferrara, M Piastra 2018 IEEE Conference on Decision and Control (CDC), 5969-5974, 2018 | 12 | 2018 |
| A 3D packaging technology for acoustically optimized integration of 2D CMUT arrays and front end circuits AS Savoia, B Mauti, G Caliano, G Matrone, M Piastra, R Bardelli, F Toia, ... 2017 IEEE International Ultrasonics Symposium (IUS), 1-4, 2017 | 12 | 2017 |
| Octupolar approximation for the excluded volume of axially symmetric convex bodies M Piastra, EG Virga Physical Review E 88 (3), 032507, 2013 | 11 | 2013 |
| Connecting social psychology and deep reinforcement learning: a probabilistic predictor on the intention to do home-based physical activity after message exposure P Catellani, V Carfora, M Piastra Frontiers in Psychology 12, 696770, 2021 | 10 | 2021 |
| A scalable multi-signal approach for the parallelization of self-organizing neural networks M Musci, G Parigi, V Cantoni, M Piastra Neural Networks 123, 108-117, 2020 | 9 | 2020 |
| Applying psychology of persuasion to conversational agents through reinforcement learning: an exploratory study. F Di Massimo, V Carfora, P Catellani, M Piastra CLiC-it, 2019 | 7 | 2019 |
| Explicit excluded volume of cylindrically symmetric convex bodies M Piastra, EG Virga Physical Review E 91 (6), 062503, 2015 | 7 | 2015 |
| A multi-signal variant for the gpu-based parallelization of growing self-organizing networks G Parigi, A Stramieri, D Pau, M Piastra Informatics in Control, Automation and Robotics: 9th International …, 2014 | 7 | 2014 |
