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Human Activity Recognition through Self-Supervised Learning

Researchers from the UK demonstrate the efficacy of self-supervised learning for human activity recognition using a vast wearable dataset. By addressing convergence issues and evaluating multi-task self-supervision, they showcase robust models with superior representation quality across diverse populations and activity types.

Deep learning-enabled system surpasses location constraints for human activity recognition

Deep learning-enabled system surpasses location constraints for human activity recognition
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CMU s Synergy Lab Unveils Trio of Ubiquitous Sensing Papers

CMU s Synergy Lab Unveils Trio of Ubiquitous Sensing Papers
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