4 papers
Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Data
Mulugeta Weldezgina Asres, Christian Walter Omlin, The CMS-HCAL Collaboration
Extracting anomaly causality facilitates diagnostics once monitoring systems detect system faults. Identifying anomaly causes in large systems involves investigating a broader set…
Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy Versus Performance
Mulugeta Weldezgina Asres, Lei Jiao, Christian Walter Omlin
Recent advancements in artificial intelligence hold ample potential for monitoring applications using surveillance cameras. However, concerns about privacy and model bias have made…
Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection
Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang +4
The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation i…
Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter
Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang +12
The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data quality mon…