MorphCL: Morphological Contrastive Learning for Inertial-based Human Activity Recognition
Despite the ubiquity of sensors in wearable and mobile devices and the abundance of human movement data they generate, translating unlabeled recordings into foundational motion models remains an open challenge. Self-supervised learning (SSL) has alleviated the need for costly annotations, yet existing approaches leave...
Marius Bock, Yu-Wei Zhang, Juergen Gall et al.
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