2 papers
cs.SD2026
Toward Faithful Explanations in Acoustic Anomaly Detection
Maab Elrashid, Anthony Deschênes, Cem Subakan +3
Interpretability is essential for user trust in real-world anomaly detection applications. However, deep learning models, despite their strong performance, often lack transparency.…
cs.SD2025
Planing It by Ear: Convolutional Neural Networks for Acoustic Anomaly Detection in Industrial Wood Planers
Anthony Deschênes, Rémi Georges, Cem Subakan +3
In recent years, the wood product industry has been facing a skilled labor shortage. The result is more frequent sudden failures, resulting in additional costs for these companies…