Scholar
Davide Dalle Pezze
Google Scholar ID: EvzyZBMAAAAJ
University of Padua
Deep Learning
Industry 4.0
Continual Learning
Visual Anomaly Detection
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Citations & Impact
All-time
Citations
175
H-index
8
i10-index
6
Publications
20
Co-authors
30
list available
Contact
Email
davide.dallepezze@dei.unipd.it
Publications
21 items
TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time Series
2026
Cited
0
AD4AD: Benchmarking Visual Anomaly Detection Models for Safer Autonomous Driving
2026
Cited
0
Continual Visual Anomaly Detection on the Edge: Benchmark and Efficient Solutions
2026
Cited
0
AdapTS: Lightweight Teacher-Student Approach for Multi-Class and Continual Visual Anomaly Detection
2026
Cited
0
Efficient Visual Anomaly Detection at the Edge: Enabling Real-Time Industrial Inspection on Resource-Constrained Devices
2026
Cited
0
VAD4Space: Visual Anomaly Detection for Planetary Surface Imagery
2026
Cited
0
MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
2026
Cited
0
Explainable Visual Anomaly Detection via Concept Bottleneck Models
2025
Cited
0
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Co-authors
13 total
Manuel Barusco
Università degli Studi di Padova
Francesco Borsatti
PhD Student, University of Padua
Elisabetta Farella
ICT Center - FBK
Francesco Paissan
Research Intern, MERL. University of Trento.
Marina Ceccon
Università degli studi di Padova
Nicola Bellotto
University of Padua
Francesco Pasti
Phd Student, Università degli Studi di Padova
Alessandro Fabris
University of Trieste
