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A Survey on Deep Learning for Human Activity Recognition.

Authors :
FUQIANG GU
MU-HUAN CHUNG
MARK CHIGNELL
SHAHROKH VALAEE
BAODING ZHOU
XUE LIU
Source :
ACM Computing Surveys; Nov2022, Vol. 54 Issue 8, p1-34, 34p
Publication Year :
2022

Abstract

Human activity recognition is a key to a lot of applications such as healthcare and smart home. In this study, we provide a comprehensive survey on recent advances and challenges in human activity recognition (HAR) with deep learning. Although there are many surveys on HAR, they focused mainly on the taxonomy of HAR and reviewed the state-of-the-art HAR systems implemented with conventional machine learning methods. Recently, several works have also been done on reviewing studies that use deep models for HAR, whereas these works cover few deep models and their variants. There is still a need for a comprehensive and in-depth survey on HAR with recently developed deep learning methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03600300
Volume :
54
Issue :
8
Database :
Complementary Index
Journal :
ACM Computing Surveys
Publication Type :
Academic Journal
Accession number :
153075410
Full Text :
https://doi.org/10.1145/3472290