| Time Series Classification Methods: Review and Applications to Power Systems Data GA Susto, A Cenedese, M Terzi Big Data Application in Power Systems, 2017 | 164 | 2017 |
| Interpretable anomaly detection with diffi: Depth-based isolation forest feature importance M Carletti, M Terzi, GA Susto arXiv preprint arXiv:2007.11117, 2020 | 109* | 2020 |
| Anomaly detection approaches for semiconductor manufacturing GA Susto, M Terzi, A Beghi Procedia Manufacturing 11, 2018-2024, 2017 | 93 | 2017 |
| Data-driven anomaly recognition for unsupervised model-free fault detection in artificial pancreas L Meneghetti, M Terzi, S Del Favero, GA Susto, C Cobelli IEEE Transactions on Control Systems Technology, 2018 | 76 | 2018 |
| A computer vision-inspired deep learning architecture for virtual metrology modeling with 2-dimensional data M Maggipinto, M Terzi, C Masiero, A Beghi, GA Susto IEEE Transactions on Semiconductor Manufacturing 31 (3), 376-384, 2018 | 65 | 2018 |
| Adversarial training reduces information and improves transferability M Terzi, A Achille, M Maggipinto, GA Susto AAAI 2021, 2020 | 27 | 2020 |
| A random forest-based approach for hand gesture recognition with wireless wearable motion capture sensors N Bargellesi, M Carletti, A Cenedese, GA Susto, M Terzi IFAC-PapersOnLine 52 (11), 128-133, 2019 | 19 | 2019 |
| Deep learning for virtual metrology: Modeling with optical emission spectroscopy data M Terzi, C Masiero, A Beghi, M Maggipinto, GA Susto 2017 IEEE 3rd International Forum on Research and Technologies for Society …, 2017 | 19 | 2017 |
| Directional adversarial training for cost sensitive deep learning classification applications M Terzi, GA Susto, P Chaudhari arXiv preprint arXiv:1910.03468, 2019 | 17 | 2019 |
| Interpretable anomaly detection with diffi: Depth-based feature importance for the isolation forest. arXiv 2020 M Carletti, M Terzi, GA Susto arXiv preprint arXiv:2007.11117, 0 | 15 | |
| A fraud detection decision support system via human on-line behavior characterization and machine learning GA Susto, M Terzi, C Masiero, S Pampuri, A Schirru 2018 First International Conference on Artificial Intelligence for …, 2018 | 14 | 2018 |
| A multivariate symbolic approach to activity recognition for wearable applications M Terzi, A Cenedese, GA Susto IFAC-PapersOnLine 50 (1), 15865-15870, 2017 | 10 | 2017 |
| Fault detection in artificial pancreas: A model-free approach L Meneghetti, M Terzi, GA Susto, S Del Favero, C Cobelli 2018 IEEE Conference on Decision and Control (CDC), 303-308, 2018 | 6 | 2018 |
| A parsimonious approach for activity recognition with wearable devices: An application to cross-country skiing A Cenedese, GA Susto, M Terzi 2016 European Control Conference (ECC), 2541-2546, 2016 | 6 | 2016 |
| β-variational classifiers under attack M Maggipinto, M Terzi, GA Susto IFAC-PapersOnLine 53 (2), 7903-7908, 2020 | 2 | 2020 |
| Robot kinematic structure classification from time series of visual data A Dalla Libera, M Terzi, A Rossi, GA Susto, R Carli 2019 18th European Control Conference (ECC), 1586-1591, 2019 | 2 | 2019 |
| Human Activity Recognition with Wearable Devices: A Symbolic Approach. A Cenedese, L Minetto, GA Susto, M Terzi PsychNology Journal 14 (2), 2016 | 2 | 2016 |
| On the limitations of adversarial training for robust image classification with convolutional neural networks M Carletti, A Sinigaglia, M Terzi, GA Susto Information Sciences 675, 120703, 2024 | 1 | 2024 |
| IntroVAC: Introspective Variational Classifiers for learning interpretable latent subspaces M Maggipinto, M Terzi, GA Susto Engineering Applications of Artificial Intelligence 109, 104658, 2022 | 1 | 2022 |
| Improving robustness with image filtering M Terzi, M Carletti, GA Susto Neurocomputing, 127927, 2024 | | 2024 |
