Selective Correlation Based Knowledge Distillation trains smaller models to accurately estimate ground reaction forces from wearable insole sensors by focusing on temporal features in correlation maps for efficient knowledge transfer.
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HCFSSNet uses convolutional layers plus a Vision Frequency State Space block with omni-directional scanning and frequency reweighting to reach competitive rate-distortion performance in learned image compression.
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Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation
Selective Correlation Based Knowledge Distillation trains smaller models to accurately estimate ground reaction forces from wearable insole sensors by focusing on temporal features in correlation maps for efficient knowledge transfer.
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A Compact Hybrid Convolution--Frequency State Space Network for Learned Image Compression
HCFSSNet uses convolutional layers plus a Vision Frequency State Space block with omni-directional scanning and frequency reweighting to reach competitive rate-distortion performance in learned image compression.