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Transfer Learning for Activity Recognition in Mobile Health
- Publication Year :
- 2020
-
Abstract
- While activity recognition from inertial sensors holds potential for mobile health, differences in sensing platforms and user movement patterns cause performance degradation. Aiming to address these challenges, we propose a transfer learning framework, TransFall, for sensor-based activity recognition. TransFall's design contains a two-tier data transformation, a label estimation layer, and a model generation layer to recognize activities for the new scenario. We validate TransFall analytically and empirically.
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2007.06062
- Document Type :
- Working Paper