Manuel Barusco

According to our database, Manuel Barusco authored at least 19 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• 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

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

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

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

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

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

Content-Based Dataset Retrieval Methods: Reproducibility of the ACORDAR Test Collection.

Laura Menotti, Manuel Barusco, Riccardo Forzan, Gianmaria Silvello

Proceedings of the Linking Theory and Practice of Digital Libraries, 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

2022

SEUPD@CLEF: Team Lgtm on Argument Retrieval for Controversial Questions.

Manuel Barusco, Gabriele Del Fiume, Riccardo Forzan, Mario Giovanni Peloso, Nicola Rizzetto, Elham Soleymani, Nicola Ferro

Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to, 2022