144 citations · 154 across the 3 of their papers we have counts for
3 papers
Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data
Hang Yuan, Shing Chan, Andrew P. Creagh +4
Advances in deep learning for human activity recognition have been relatively limited due to the lack of large labelled datasets. In this study, we leverage self-supervised learnin…
IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition
Hyeokhyen Kwon, Catherine Tong, Harish Haresamudram +4
The lack of large-scale, labeled data sets impedes progress in developing robust and generalized predictive models for on-body sensor-based human activity recognition (HAR). Labele…
Are Accelerometers for Activity Recognition a Dead-end?
Catherine Tong, Shyam A. Tailor, Nicholas D. Lane
Accelerometer-based (and by extension other inertial sensors) research for Human Activity Recognition (HAR) is a dead-end. This sensor does not offer enough information for us to p…