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cs.CV2025
Multi-Flow: Multi-View-Enriched Normalizing Flows for Industrial Anomaly Detection
Mathis Kruse, Bodo Rosenhahn
With more well-performing anomaly detection methods proposed, many of the single-view tasks have been solved to a relatively good degree. However, real-world production scenarios o…
cs.LG2025
AutoML for Multi-Class Anomaly Compensation of Sensor Drift
Melanie Schaller, Mathis Kruse, Antonio Ortega +2
Addressing sensor drift is essential in industrial measurement systems, where precise data output is necessary for maintaining accuracy and reliability in monitoring processes, as…