Davide Dalle Pezze

According to our database, Davide Dalle Pezze authored at least 20 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Teach YOLO to Remember: A Self-Distillation Approach for Continual Object Detection.

Riccardo De Monte, Davide Dalle Pezze, Gian Antonio Susto

CoRR, March, 2025

Memory Efficient Continual Learning for Edge-Based Visual Anomaly Detection.

Manuel Barusco, Lorenzo D'Antoni, Davide Dalle Pezze, Francesco Borsatti, Gian Antonio Susto

CoRR, March, 2025

From Vision to Sound: Advancing Audio Anomaly Detection with Vision-Based Algorithms.

Manuel Barusco, Francesco Borsatti, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto

CoRR, February, 2025

2024

Continual Learning for Behavior-based Driver Identification.

Mattia Fanan, Davide Dalle Pezze, Emad Efatinasab, Ruggero Carli, Mirco Rampazzo, Gian Antonio Susto

CoRR, 2024

PaSTe: Improving the Efficiency of Visual Anomaly Detection at the Edge.

Manuel Barusco, Francesco Borsatti, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto

CoRR, 2024

Tiny Robotics Dataset and Benchmark for Continual Object Detection.

Francesco Pasti, Riccardo De Monte, Davide Dalle Pezze, Gian Antonio Susto, Nicola Bellotto

CoRR, 2024

Replay Consolidation with Label Propagation for Continual Object Detection.

Riccardo De Monte, Davide Dalle Pezze, Marina Ceccon, Francesco Pasti, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto, Nicola Bellotto

CoRR, 2024

Latent Distillation for Continual Object Detection at the Edge.

Francesco Pasti, Marina Ceccon, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto, Nicola Bellotto

CoRR, 2024

Fairness Evolution in Continual Learning for Medical Imaging.

Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, Gian Antonio Susto

CoRR, 2024

Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark.

Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, Gian Antonio Susto

CoRR, 2024

Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient Descent.

Luca Della Libera, Jacopo Andreoli, Davide Dalle Pezze, Mirco Ravanelli, Gian Antonio Susto

CoRR, 2024

An empirical evaluation of tinyML architectures for Class-Incremental Continual Learning.

Matteo Tremonti, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2024

Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning.

Nikola Bugarin, Jovana Bugaric, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

AcME - Accelerated model-agnostic explanations: Fast whitening of the machine-learning black box.

David Dandolo, Chiara Masiero, Mattia Carletti, Davide Dalle Pezze, Gian Antonio Susto

Expert Syst. Appl., 2023

A multi-label Continual Learning framework to scale deep learning approaches for packaging equipment monitoring.

Davide Dalle Pezze, Denis Deronjic, Chiara Masiero, Diego Tosato, Alessandro Beghi, Gian Antonio Susto

Eng. Appl. Artif. Intell., 2023

Predictive Maintenance in the Industry: A Comparative Study on Deep Learning-based Remaining Useful Life Estimation.

Luciano Lorenti, Davide Dalle Pezze, Jacopo Andreoli, Chiara Masiero, Natalie Gentner, Yao Yang, Gian Antonio Susto

Proceedings of the 21st IEEE International Conference on Industrial Informatics, 2023

VIR2EM: VIrtualization and Remotization for Resilient and Efficient Manufacturing: Project-Dissemination Paper.

Alessandro Beghi, Nicola Dall'Ora, Davide Dalle Pezze, Franco Fummi, Chiara Masiero, Stefano Spellini, Gian Antonio Susto, Francesco Tosoni

Proceedings of the Forum on Specification & Design Languages, 2023

2022

Alarm Logs in Packaging Industry (ALPI).

Diego Tosato, Davide Dalle Pezze, Chiara Masiero, Gian Antonio Susto, Alessandro Beghi

Dataset, May, 2022

FORMULA: A Deep Learning Approach for Rare Alarms Predictions in Industrial Equipment.

Davide Dalle Pezze, Chiara Masiero, Diego Tosato, Alessandro Beghi, Gian Antonio Susto

IEEE Trans Autom. Sci. Eng., 2022

Continual Learning Approaches for Anomaly Detection.

Davide Dalle Pezze, Eugenia Anello, Chiara Masiero, Gian Antonio Susto

CoRR, 2022