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Self-supervised learning for human activity recognition using 700,000 person-days of wearable data

Computer Science

Self-supervised learning for human activity recognition using 700,000 person-days of wearable data

H. Yuan, S. Chan, et al.

Discover how Hang Yuan, Shing Chan, Andrew P. Creagh, and their colleagues are revolutionizing human activity recognition with self-supervised learning techniques applied to a massive dataset from the UK Biobank. Their models not only achieve remarkable accuracy but also generalize across various environments and devices, paving the way for advancements in fields with limited labeled data.

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