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Sparse fusion in RGB-T detection slashes computational costs while preserving accuracy, enabling efficient processing of high-resolution images.
Extracting and clustering independent components from EEG data reveals stable neural signatures of emergency braking, enabling more accurate braking intensity prediction.
