Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems 2023
DOI: 10.1145/3625687.3625782
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MESEN: Exploit Multimodal Data to Design Unimodal Human Activity Recognition with Few Labels

Lilin Xu,
Chaojie Gu,
Rui Tan
et al.

Abstract: Human activity recognition (HAR) will be an essential function of various emerging applications. However, HAR typically encounters challenges related to modality limitations and label scarcity, leading to an application gap between current solutions and real-world requirements. In this work, we propose MESEN, a multimodalempowered unimodal sensing framework, to utilize unlabeled multimodal data available during the HAR model design phase for unimodal HAR enhancement during the deployment phase. From a study on… Show more

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Cited by 6 publications
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