Vitolo, Paola
Vitolo, Paola
Dipartimento di Ingegneria Industriale/DIIN
A 0.8 mW TinyML-Based PDM-to-PCM Conversion for In-Sensor KWS Applications
2022-01-01 Vitolo, P.; Liguori, R.; Di Benedetto, L.; Rubino, A.; Pau, D.; Licciardo, G. D.
A New NN-Based Approach to In-Sensor PDM-to-PCM Conversion for Ultra TinyML KWS
2023-01-01 Vitolo, P.; Liguori, R.; Di Benedetto, L.; Rubino, A.; Pau, D.; Licciardo, G. D.
In-Sensor System for Real-Time Compensation of Thermal Drift in MEMS Pressure Sensors
2024-01-01 Vitolo, P.; Licciardo, G. D.; Liguori, R.; Di Benedetto, L.; Rubino, A.; Pau, D.; Pesaturo, M.
Low-complexity Machine Learning Architecture for Hardware-aware True Random Number Generators Assessment and Continuous Monitoring
2023-01-01 Spinelli, F.; Moretti, R.; Addabbo, T.; Vitolo, P.; Licciardo, G. D.
Low-Power Anomaly Detection and Classification System based on a Partially Binarized Autoencoder for In-Sensor Computing
2021-01-01 Vitolo, P.; Licciardo, G. D.; Di Benedetto, L.; Liguori, R.; Rubino, A.; Pau, D.
Low-Power Detection and Classification for In-sensor Predictive Maintenance based on Vibration Monitoring
2022-01-01 Vitolo, Paola; De Vita, Antonio; DI BENEDETTO, Luigi; Pau, Danilo; Licciardo, Gian Domenico
Quantized ID-CNN for a Low-power PDM-to-PCM Conversion in TinyML KWS Applications
2022-01-01 Vitolo, P.; Licciardo, G. D.; Amendola, A. C.; Di Benedetto, L.; Liguori, R.; Rubino, A.; Pau, D.
Tiny compensation of pressure drift measurements due to long exposures to high temperatures
2023-01-01 Vitolo, P.; Pau, D.; Licciardo, G. D.; Pesaturo, M.; Bosco, S.; Pennino, S.
Tiny Machine Learning Zoo for Long-Term Compensation of Pressure Sensor Drifts
2023-01-01 Pau, D.; Ben Yahmed, W.; Aymone, F. M.; Licciardo, G. D.; Vitolo, P.
Ultra-Tiny Neural Network for Compensation of Post-soldering Thermal Drift in MEMS Pressure Sensors
2023-01-01 Licciardo, G. D.; Vitolo, P.; Bosco, S.; Pennino, S.; Pau, D.; Pesaturo, M.; Di Benedetto, L.; Liguori, R.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| A 0.8 mW TinyML-Based PDM-to-PCM Conversion for In-Sensor KWS Applications | 1-gen-2022 | Vitolo, P.; Liguori, R.; Di Benedetto, L.; Rubino, A.; Pau, D.; Licciardo, G. D. | |
| A New NN-Based Approach to In-Sensor PDM-to-PCM Conversion for Ultra TinyML KWS | 1-gen-2023 | Vitolo, P.; Liguori, R.; Di Benedetto, L.; Rubino, A.; Pau, D.; Licciardo, G. D. | |
| In-Sensor System for Real-Time Compensation of Thermal Drift in MEMS Pressure Sensors | 1-gen-2024 | Vitolo, P.; Licciardo, G. D.; Liguori, R.; Di Benedetto, L.; Rubino, A.; Pau, D.; Pesaturo, M. | |
| Low-complexity Machine Learning Architecture for Hardware-aware True Random Number Generators Assessment and Continuous Monitoring | 1-gen-2023 | Spinelli, F.; Moretti, R.; Addabbo, T.; Vitolo, P.; Licciardo, G. D. | |
| Low-Power Anomaly Detection and Classification System based on a Partially Binarized Autoencoder for In-Sensor Computing | 1-gen-2021 | Vitolo, P.; Licciardo, G. D.; Di Benedetto, L.; Liguori, R.; Rubino, A.; Pau, D. | |
| Low-Power Detection and Classification for In-sensor Predictive Maintenance based on Vibration Monitoring | 1-gen-2022 | Vitolo, Paola; De Vita, Antonio; DI BENEDETTO, Luigi; Pau, Danilo; Licciardo, Gian Domenico | |
| Quantized ID-CNN for a Low-power PDM-to-PCM Conversion in TinyML KWS Applications | 1-gen-2022 | Vitolo, P.; Licciardo, G. D.; Amendola, A. C.; Di Benedetto, L.; Liguori, R.; Rubino, A.; Pau, D. | |
| Tiny compensation of pressure drift measurements due to long exposures to high temperatures | 1-gen-2023 | Vitolo, P.; Pau, D.; Licciardo, G. D.; Pesaturo, M.; Bosco, S.; Pennino, S. | |
| Tiny Machine Learning Zoo for Long-Term Compensation of Pressure Sensor Drifts | 1-gen-2023 | Pau, D.; Ben Yahmed, W.; Aymone, F. M.; Licciardo, G. D.; Vitolo, P. | |
| Ultra-Tiny Neural Network for Compensation of Post-soldering Thermal Drift in MEMS Pressure Sensors | 1-gen-2023 | Licciardo, G. D.; Vitolo, P.; Bosco, S.; Pennino, S.; Pau, D.; Pesaturo, M.; Di Benedetto, L.; Liguori, R. |