survey

A Survey on Deep Learning for Human Activity Recognition

Authors:

Shahrokh Valaee,

Xue LiuAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 54, Issue 8

Article No.: 177, Pages 1 - 34

https://doi.org/10.1145/3472290

Published: 04 October 2021 Publication History

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.

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Index Terms

A Survey on Deep Learning for Human Activity Recognition
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 54, Issue 8

November 2022

754 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3481697

Editor:
Albert Zomaya
University of Sydney, Australia

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Publication History

Published: 04 October 2021

Accepted: 01 June 2021

Revised: 01 June 2021

Received: 01 June 2020

Published in CSUR Volume 54, Issue 8

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https://doi.org/10.37394/232018.2024.12.24
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https://dl.acm.org/doi/10.1155/2024/1832298
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Ahmad IUllah AChoi W(2024)WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and OpportunitiesIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34115295(3595-3623)Online publication date: 2024
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