Davide Dalle Pezze

According to our database, Davide Dalle Pezze authored at least 37 papers between 2022 and 2026.

Collaborative distances:

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

2026

Deep Learning for Virtual Reality User Identification: A Benchmark.

Davide Frizzo, Fabrizio Genilotti, David Petrovic, Arianna Stropeni, Francesco Borsatti, Davide Dalle Pezze, Riccardo De Monte, Manuel Barusco, Gian Antonio Susto

CoRR, April, 2026

AD4AD: Benchmarking Visual Anomaly Detection Models for Safer Autonomous Driving.

Fabrizio Genilotti, Arianna Stropeni, Gionata Grotto, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto

CoRR, April, 2026

Continual Visual Anomaly Detection on the Edge: Benchmark and Efficient Solutions.

Manuel Barusco, Francesco Borsatti, David Petrovic, Davide Dalle Pezze, Gian Antonio Susto

CoRR, April, 2026

Efficient Visual Anomaly Detection at the Edge: Enabling Real-Time Industrial Inspection on Resource-Constrained Devices.

Arianna Stropeni, Fabrizio Genilotti, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto

CoRR, March, 2026

AdapTS: Lightweight Teacher-Student Approach for Multi-Class and Continual Visual Anomaly Detection.

Manuel Barusco, Davide Dalle Pezze, Francesco Borsatti, Gian Antonio Susto

CoRR, March, 2026

VAD4Space: Visual Anomaly Detection for Planetary Surface Imagery.

Fabrizio Genilotti, Arianna Stropeni, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto

CoRR, March, 2026

MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection.

Jinwei Hu, Francesco Borsatti, Arianna Stropeni, Davide Dalle Pezze, Manuel Barusco, Gian Antonio Susto

CoRR, March, 2026

Guest Editorial:Beyond Classic Deep Learning: Algorithms for Dealing With Real-World Applications in Industrial Automation.

Gian Antonio Susto, Olga Fink, Seokho Kang, Lars Mönch, Davide Dalle Pezze

IEEE Trans Autom. Sci. Eng., 2026

Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing.

Adrian Poniatowski, Natalie Gentner, Manuel Barusco, Davide Dalle Pezze, Samuele Salti, Gian Antonio Susto

IEEE Trans Autom. Sci. Eng., 2026

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

IEEE Trans Autom. Sci. Eng., 2026

2025

Continual learning approaches for anomaly detection.

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

Evol. Syst., December, 2025

Explainable Visual Anomaly Detection via Concept Bottleneck Models.

Arianna Stropeni, Valentina Zaccaria, Francesco Borsatti, Davide Dalle Pezze, Manuel Barusco, Gian Antonio Susto

CoRR, November, 2025

ProDER: A Continual Learning Approach for Fault Prediction in Evolving Smart Grids.

Emad Efatinasab, Nahal Azadi, Davide Dalle Pezze, Gian Antonio Susto, Chuadhry Mujeeb Ahmed, Mirco Rampazzo

CoRR, November, 2025

Towards Continual Visual Anomaly Detection in the Medical Domain.

Manuel Barusco, Francesco Borsatti, Nicola Beda, Davide Dalle Pezze, Gian Antonio Susto

CoRR, August, 2025

MoViAD: A Modular Library for Visual Anomaly Detection.

Manuel Barusco, Francesco Borsatti, Arianna Stropeni, Davide Dalle Pezze, Gian Antonio Susto

CoRR, July, 2025

Evaluating Modern Visual Anomaly Detection Approaches in Semiconductor Manufacturing: A Comparative Study.

Manuel Barusco, Francesco Borsatti, Youssef Ben Khalifa, Davide Dalle Pezze, Gian Antonio Susto

CoRR, May, 2025

Towards Scalable IoT Deployment for Visual Anomaly Detection via Efficient Compression.

Arianna Stropeni, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Marco Fabris, Gian Antonio Susto

CoRR, May, 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

Underrepresentation, label bias, and proxies: Towards Data Bias Profiles for the EU AI act and beyond.

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

Expert Syst. Appl., 2025

Continual Learning for Behavior-based Driver Identification.

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

Eng. Appl. Artif. Intell., 2025

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

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

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

Is Underrepresentation overemphasized? A study of data bias and algorithmic fairness.

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

Proceedings of the Joint Proceedings of the Thematic Workshops at Ital-IA 2025 colocated with the 5th National Conference on Artificial Intelligence, 2025

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

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

Fairness Evolution in Continual Learning for Medical Imaging.

Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, 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

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

Proceedings of the Computer Vision - ECCV 2024 Workshops, 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