面向人类活动识别的深度学习研究综述

Fuqiang Gu, Mu-Huan Chung, M. Chignell, S. Valaee, Baoding Zhou, Xue Liu
{"title":"面向人类活动识别的深度学习研究综述","authors":"Fuqiang Gu, Mu-Huan Chung, M. Chignell, S. Valaee, Baoding Zhou, Xue Liu","doi":"10.1145/3472290","DOIUrl":null,"url":null,"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.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"2018 1","pages":"1 - 34"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"82","resultStr":"{\"title\":\"A Survey on Deep Learning for Human Activity Recognition\",\"authors\":\"Fuqiang Gu, Mu-Huan Chung, M. Chignell, S. Valaee, Baoding Zhou, Xue Liu\",\"doi\":\"10.1145/3472290\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":7000,\"journal\":{\"name\":\"ACM Computing Surveys (CSUR)\",\"volume\":\"2018 1\",\"pages\":\"1 - 34\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"82\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Computing Surveys (CSUR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3472290\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys (CSUR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3472290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 82

摘要

人类活动识别是医疗保健和智能家居等许多应用的关键。在本研究中,我们对深度学习在人类活动识别(HAR)方面的最新进展和挑战进行了全面调查。虽然有很多关于HAR的调查,但他们主要关注HAR的分类,并回顾了使用传统机器学习方法实现的最先进的HAR系统。最近,也有一些研究对使用深度模型进行HAR的研究进行了回顾,然而这些研究只涵盖了很少的深度模型及其变体。目前仍有必要利用最近发展的深度学习方法对HAR进行全面而深入的调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Deep Learning for Human Activity Recognition
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信