Formalizes suicide risk assessment (SRA) from metro videos and benchmarks an interpretable pipeline with 83.2% ROC-AUC using tracking, activity recognition, segmentation, and risk heatmaps.
Boring, and Anahita Khojandi
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Suicide Risk Assessment from AI-powered Video Surveillance: An Interpretable Framework for Prevention in Metro Stations
Formalizes suicide risk assessment (SRA) from metro videos and benchmarks an interpretable pipeline with 83.2% ROC-AUC using tracking, activity recognition, segmentation, and risk heatmaps.