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ORCIDManuel Barusco
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2020 – today
- 2026
[j1]Adrian Poniatowski, Natalie Gentner
, Manuel Barusco, Davide Dalle Pezze, Samuele Salti, Gian Antonio Susto:
Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing. IEEE Trans Autom. Sci. Eng. 23: 3818-3828 (2026)- [i17]Jinwei Hu, Francesco Borsatti, Arianna Stropeni, Davide Dalle Pezze, Manuel Barusco, Gian Antonio Susto:
MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection. CoRR abs/2603.13507 (2026) - [i16]Fabrizio Genilotti, Arianna Stropeni, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto:
VAD4Space: Visual Anomaly Detection for Planetary Surface Imagery. CoRR abs/2603.13993 (2026) - [i15]Manuel Barusco, Davide Dalle Pezze, Francesco Borsatti, Gian Antonio Susto:
AdapTS: Lightweight Teacher-Student Approach for Multi-Class and Continual Visual Anomaly Detection. CoRR abs/2603.17530 (2026) - [i14]Arianna Stropeni, Fabrizio Genilotti, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto:
Efficient Visual Anomaly Detection at the Edge: Enabling Real-Time Industrial Inspection on Resource-Constrained Devices. CoRR abs/2603.20288 (2026) - [i13]Manuel Barusco, Francesco Borsatti, David Petrovic, Davide Dalle Pezze, Gian Antonio Susto:
Continual Visual Anomaly Detection on the Edge: Benchmark and Efficient Solutions. CoRR abs/2604.06435 (2026) - [i12]Fabrizio Genilotti, Arianna Stropeni, Gionata Grotto, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto:
AD4AD: Benchmarking Visual Anomaly Detection Models for Safer Autonomous Driving. CoRR abs/2604.15291 (2026) - [i11]Davide Frizzo, Fabrizio Genilotti, David Petrovic, Arianna Stropeni, Francesco Borsatti, Davide Dalle Pezze, Riccardo De Monte, Manuel Barusco, Gian Antonio Susto:
Deep Learning for Virtual Reality User Identification: A Benchmark. CoRR abs/2604.16341 (2026) - 2025
- [c4]Manuel Barusco, Francesco Borsatti, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto:
PaSTe: Improving the Efficiency of Visual Anomaly Detection at the Edge. CVPR Workshops 2025: 4026-4035 - [i10]Manuel Barusco, Francesco Borsatti, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto:
From Vision to Sound: Advancing Audio Anomaly Detection with Vision-Based Algorithms. CoRR abs/2502.18328 (2025) - [i9]Manuel Barusco, Lorenzo D'Antoni, Davide Dalle Pezze, Francesco Borsatti, Gian Antonio Susto:
Memory Efficient Continual Learning for Edge-Based Visual Anomaly Detection. CoRR abs/2503.02691 (2025) - [i8]Arianna Stropeni, Francesco Borsatti, Manuel Barusco, Davide Dalle Pezze, Marco Fabris, Gian Antonio Susto:
Towards Scalable IoT Deployment for Visual Anomaly Detection via Efficient Compression. CoRR abs/2505.07119 (2025) - [i7]Manuel Barusco, Francesco Borsatti, Youssef Ben Khalifa, Davide Dalle Pezze, Gian Antonio Susto:
Evaluating Modern Visual Anomaly Detection Approaches in Semiconductor Manufacturing: A Comparative Study. CoRR abs/2505.07576 (2025) - [i6]Adrian Poniatowski, Natalie Gentner, Manuel Barusco, Davide Dalle Pezze, Samuele Salti, Gian Antonio Susto:
Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing. CoRR abs/2506.15260 (2025) - [i5]Manuel Barusco, Francesco Borsatti, Arianna Stropeni, Davide Dalle Pezze, Gian Antonio Susto:
MoViAD: A Modular Library for Visual Anomaly Detection. CoRR abs/2507.12049 (2025) - [i4]Manuel Barusco, Francesco Borsatti, Nicola Beda, Davide Dalle Pezze, Gian Antonio Susto:
Towards Continual Visual Anomaly Detection in the Medical Domain. CoRR abs/2508.18013 (2025) - [i3]Arianna Stropeni, Valentina Zaccaria, Francesco Borsatti, Davide Dalle Pezze, Manuel Barusco, Gian Antonio Susto:
Explainable Visual Anomaly Detection via Concept Bottleneck Models. CoRR abs/2511.20088 (2025) - 2024
- [c3]Nikola Bugarin, Jovana Bugaric, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto:
Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning. CVPR Workshops 2024: 4065-4074 - [c2]Laura Menotti, Manuel Barusco, Riccardo Forzan, Gianmaria Silvello:
Content-Based Dataset Retrieval Methods: Reproducibility of the ACORDAR Test Collection. TPDL (1) 2024: 310-325 - [i2]Nikola Bugarin, Jovana Bugaric, Manuel Barusco, Davide Dalle Pezze, Gian Antonio Susto:
Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning. CoRR abs/2403.15463 (2024) - [i1]Manuel Barusco, Francesco Borsatti, Davide Dalle Pezze, Francesco Paissan, Elisabetta Farella, Gian Antonio Susto:
PaSTe: Improving the Efficiency of Visual Anomaly Detection at the Edge. CoRR abs/2410.11591 (2024) - 2022
- [c1]Manuel Barusco, Gabriele Del Fiume, Riccardo Forzan, Mario Giovanni Peloso, Nicola Rizzetto, Elham Soleymani, Nicola Ferro:
SEUPD@CLEF: Team Lgtm on Argument Retrieval for Controversial Questions. CLEF (Working Notes) 2022: 2933-2955
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