Institute of Computing Technology, Chinese Academy IR
Deep learning for sensor-based activity recognition: A survey | |
Wang, Jindong1,2; Chen, Yiqiang1,2; Hao, Shuji3; Peng, Xiaohui1,2; Hu, Lisha1,2 | |
2019-03-01 | |
发表期刊 | PATTERN RECOGNITION LETTERS
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ISSN | 0167-8655 |
卷号 | 119页码:3-11 |
摘要 | Sensor-based activity recognition seeks the profound high-level knowledge about human activities from multitudes of low-level sensor readings. Conventional pattern recognition approaches have made tremendous progress in the past years. However, those methods often heavily rely on heuristic hand-crafted feature extraction, which could hinder their generalization performance. Additionally, existing methods are undermined for unsupervised and incremental learning tasks. Recently, the recent advancement of deep learning makes it possible to perform automatic high-level feature extraction thus achieves promising performance in many areas. Since then, deep learning based methods have been widely adopted for the sensor-based activity recognition tasks. This paper surveys the recent advance of deep learning based sensor-based activity recognition. We summarize existing literature from three aspects: sensor modality, deep model, and application. We also present detailed insights on existing work and propose grand challenges for future research. (C) 2018 Elsevier B.V. All rights reserved. |
关键词 | Deep learning Activity recognition Pattern recognition Pervasive computing |
DOI | 10.1016/j.patrec.2018.02.010 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research & Development Program of China[2017YFB1002801] ; NSFC[61572471] ; Science and Technology Planning Project of Guangdong Province[2015B010105001] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000458876700002 |
出版者 | ELSEVIER SCIENCE BV |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/3401 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Chen, Yiqiang |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.ASTAR, Inst High Performance Comp, Singapore, Singapore |
推荐引用方式 GB/T 7714 | Wang, Jindong,Chen, Yiqiang,Hao, Shuji,et al. Deep learning for sensor-based activity recognition: A survey[J]. PATTERN RECOGNITION LETTERS,2019,119:3-11. |
APA | Wang, Jindong,Chen, Yiqiang,Hao, Shuji,Peng, Xiaohui,&Hu, Lisha.(2019).Deep learning for sensor-based activity recognition: A survey.PATTERN RECOGNITION LETTERS,119,3-11. |
MLA | Wang, Jindong,et al."Deep learning for sensor-based activity recognition: A survey".PATTERN RECOGNITION LETTERS 119(2019):3-11. |
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