2 papers
cs.CV2026
Explainable Visual Anomaly Detection via Concept Bottleneck Models
Arianna Stropeni, Valentina Zaccaria, Francesco Borsatti +3
In recent years, Visual Anomaly Detection (VAD) has gained significant attention due to its ability to identify defects using only normal images during training. Many VAD models wo…
cs.LG2024
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-AD
Valentina Zaccaria, Chiara Masiero, David Dandolo +1
While Machine Learning has become crucial for Industry 4.0, its opaque nature hinders trust and impedes the transformation of valuable insights into actionable decision, a challeng…