A dual-path ResNet/DenseNet framework with multi-stage contrastive learning and confidence-driven gradient modulation is presented for multimodal human activity recognition, with reported improvements on four public datasets.
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Confidence-driven Gradient Modulation for Multimodal Human Activity Recognition: A Dynamic Contrastive Dual-Path Learning Approach
A dual-path ResNet/DenseNet framework with multi-stage contrastive learning and confidence-driven gradient modulation is presented for multimodal human activity recognition, with reported improvements on four public datasets.