Abstract: Training deep reinforcement learning (DRL) agents for fault detection in microgrids requires significant computational resources and time, particularly for dense neural networks. This paper ...
Abstract: Weakly supervised video anomaly detection has gained attention for its effective performance and cost-efficient annotation, using video-level labels to distinguish between normal and ...
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