What is it about?
SelfHAR is a new way to train a deep learning model for detecting user's activity by using data that are collected passively in the background, in addition to data that need to be annotated by experts.
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Why is it important?
This framework can reduce the amount of data that need to be annotated by experts for mobile sensing, which tend to be expensive. It also exposes the models to a wider range of data.
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This page is a summary of: SelfHAR, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, March 2021, ACM (Association for Computing Machinery),
DOI: 10.1145/3448112.
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