| A comparative study of machine learning algorithms for physiological signal classification G Biagetti, P Crippa, L Falaschetti, G Tanoni, C Turchetti Procedia computer science 126, 1977-1984, 2018 | 32 | 2018 |
| Multilabel appliance classification with weakly labeled data for non-intrusive load monitoring G Tanoni, E Principi, S Squartini IEEE Transactions on Smart Grid 14 (1), 440-452, 2022 | 19 | 2022 |
| Improving knowledge distillation for non-intrusive load monitoring through explainability guided learning D Batic, G Tanoni, L Stankovic, V Stankovic, E Principi ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 8 | 2023 |
| A multiple instance regression approach to electrical load disaggregation L Serafini, G Tanoni, E Principi, S Spinsante, S Squartini 2022 30th European Signal Processing Conference (EUSIPCO), 1666-1670, 2022 | 7 | 2022 |
| Weakly supervised transfer learning for multi-label appliance classification G Tanoni, E Principi, L Mandolini, S Squartini International Conference on Applied Intelligence and Informatics, 360-375, 2022 | 4 | 2022 |
| Knowledge distillation for scalable nonintrusive load monitoring G Tanoni, L Stankovic, V Stankovic, S Squartini, E Principi IEEE Transactions on Industrial Informatics, 2023 | 1 | 2023 |
| Non-Intrusive Load Monitoring in industrial settings: A systematic review G Tanoni, E Principi, S Squartini Renewable and Sustainable Energy Reviews 202, 114703, 2024 | | 2024 |
| A weakly supervised active learning framework for non-intrusive load monitoring G Tanoni, T Sobot, E Principi, V Stankovic, L Stankovic, S Squartini Integrated Computer-Aided Engineering, 1-18, 2024 | | 2024 |
| Deep Learning Techniques for Edge-Centric Non-Intrusive Load Monitoring G Tanoni Università Politecnica delle Marche, 2024 | | 2024 |
| Appliance-Incremental Learning for Non-Intrusive Load Monitoring G Tanoni, E Principi, L Mandoliniy, S Squartini 2023 IEEE International Conference on Communications, Control, and Computing …, 2023 | | 2023 |
| A SPIKING NEURAL NETWORK BASED APPROACH FOR BINAURAL SOUND LOCALIZATION G Tanoni | | 2019 |
Emanuele PrincipiUniversità Politecnica delle Marche在 univpm.it 的电子邮件经过验证
