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A Novel Feature Incremental Learning Method for Sensor-Based Activity Recognition

文献类型：期刊论文

作者Hu, Chunyu4,5,6; Yu, Han1,2,3; Peng, Xiaohui4,5,6; Chen, Yiqiang4,5,6; Gao, Chenlong4,5,6; Hu, Lisha4,5,6
刊名IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
出版日期2019-06-01
卷号31期号:6页码:1038-1050
关键词Feature incremental learning activity recognition random forest
ISSN号1041-4347
DOI10.1109/TKDE.2018.2855159
英文摘要Recognizing activities of daily living is an important research topic for health monitoring and elderly care. However, most existing activity recognition models only work with static and pre-defined sensor configurations. Enabling an existing activity recognition model to adapt to the emergence of new sensors in a dynamic environment is a significant challenge. In this paper, we propose a novel feature incremental learning method, namely the Feature Incremental Random Forest (FIRF), to improve the performance of an existing model with a small amount of data on newly appeared features. It consists of two important components - 1) a mutual information based diversity generation strategy (MIDGS) and 2) a feature incremental tree growing mechanism (FITGM). MIDGS enhances the internal diversity of random forests, while FITGM improves the accuracy of individual decision trees. To evaluate the performance of FIRF, we conduct extensive experiments on three well-known public datasets for activity recognition. Experimental results demonstrate that FIRF is significantly more accurate and efficient compared with other state-of-the-art methods. It has the potential to allow the dynamic exploitation of new sensors in changing environments.
资助项目National Key Research and Development Plan of China[2017YFB1002801] ; Natural Science Foundation of China[61572471] ; Natural Science Foundation of China[61502456] ; Natural Science Foundation of China[61472399] ; Beijing Municipal Science & Technology Commission[Z161100000216140] ; Nanyang Technological University, Nanyang Assistant Professorship (NAP)
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000466933700002
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/4237]  
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.Alibaba NTU Singapore Joint Res Inst, Singapore 639798, Singapore
2.NTU UBC Res Ctr Excellence Act Living Elderly LIL, Singapore 639798, Singapore
3.Nanyang Technol Univ, SCSE, Singapore 639798, Singapore
4.Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
6.Chinese Acad Sci, Inst Comp Technol, Beijing 100864, Peoples R China
推荐引用方式
GB/T 7714		 Hu, Chunyu,Yu, Han,Peng, Xiaohui,et al. A Novel Feature Incremental Learning Method for Sensor-Based Activity Recognition[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2019,31(6):1038-1050.
APA Hu, Chunyu,Yu, Han,Peng, Xiaohui,Chen, Yiqiang,Gao, Chenlong,&Hu, Lisha.(2019).A Novel Feature Incremental Learning Method for Sensor-Based Activity Recognition.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,31(6),1038-1050.
MLA Hu, Chunyu,et al."A Novel Feature Incremental Learning Method for Sensor-Based Activity Recognition".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 31.6(2019):1038-1050.

入库方式： OAI收割

来源：计算技术研究所

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