AI RESEARCH
Triple Spectral Fusion for Sensor-based Human Activity Recognition
arXiv CS.CV
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ArXi:2605.02743v1 Announce Type: cross The field of sensor-based human activity recognition (HAR) mainly uses posture, motion and context data of Inertial Measurement Units (IMUs) to identify daily activities. Despite the advancements in learning-based methods, it is challenging to perform information fusion from the temporal perspective due to the complexities in fusing heterogeneous sensor data and establishing long-term context correlations. This paper proposes a novel triple spectral fusion framework tailored for.