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

, , , , , , and . npj Digit. Medicine, (2024)

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IMUTube: Automatic extraction of virtual on-body accelerometry from video for human activity recognition., , , , , , and . CoRR, (2020)Self-supervised Learning for Human Activity Recognition Using 700, 000 Person-days of Wearable Data., , , , , and . CoRR, (2022)RainBench: Towards Global Precipitation Forecasting from Satellite Imagery., , , , , , , and . CoRR, (2020)Deterministic Binary Filters for Convolutional Neural Networks., , , , , and . IJCAI, page 2739-2747. ijcai.org, (2018)Are Accelerometers for Activity Recognition a Dead-end?, , and . HotMobile, page 39-44. ACM, (2020)Self-supervised learning for human activity recognition using 700,000 person-days of wearable data., , , , , , and . npj Digit. Medicine, (2024)Can You See It?: Good, So We Can Sense It!, , , , , , and . GetMobile Mob. Comput. Commun., 25 (2): 38-42 (2021)Predicting Patient Outcomes with Graph Representation Learning., , , , and . CoRR, (2021)Multimodal Deep Learning for Activity and Context Recognition., , , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 1 (4): 157:1-157:27 (2017)Tracking Fatigue and Health State in Multiple Sclerosis Patients Using Connnected Wellness Devices., , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 3 (3): 106:1-106:19 (2019)