ECoLAD shows classical anomaly detectors maintain coverage and accuracy lift under automotive compute limits while several deep methods lose feasibility first.
Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding
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ECoLAD: Deployment-Oriented Evaluation for Automotive Time-Series Anomaly Detection
ECoLAD shows classical anomaly detectors maintain coverage and accuracy lift under automotive compute limits while several deep methods lose feasibility first.