OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition
文献类型：期刊论文
| 作者 | Hu, Lisha1,2,3; Chen, Yiqiang1,2,3; Wang, Jindong1,2,3; Hu, Chunyu1,2,3; Jiang, Xinlong1,2,3 |
| 刊名 | INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
 |
| 出版日期 | 2018-09-01 |
| 卷号 | 9期号:9页码:1577-1590 |
| 关键词 | Extreme learning machine Kernel Activity recognition Online learning Wearable computing |
| ISSN号 | 1868-8071 |
| DOI | 10.1007/s13042-017-0666-8 |
| 英文摘要 | Miscellaneous mini-wearable devices (Jawbone Up, Apple Watch, Google Glass, et al.) have emerged in recent years to recognize the user's activities of daily living (ADLs) such as walking, running, climbing and bicycling. To better suits a target user, a generic activity recognition (AR) model inside the wearable devices requires to adapt itself according to the user's personality in terms of wearing styles and so on. In this paper, an online kernelized and regularized extreme learning machine (OKRELM) is proposed for wearable-based activity recognition. A small-scale but important subset of every incoming data chunk is chosen to go through the update stage during the online sequential learning. Therefore, OKRELM is a lightweight incremental learning model with less time consumption during the update and prediction phase, a robust and effective classifier compared with the batch learning scheme. The performance of OKRELM is evaluated and compared with several related approaches on a UCI online available AR dataset and experimental results show the efficiency and effectiveness of OKRELM. |
| 资助项目 | Natural Science Foundation of China[61572471] ; Natural Science Foundation of China[61210010] ; Chinese Academy of Sciences Research Equipment Development Project[YZ201527] ; Science and Technology Planning Project of Guangdong Province[2015B010105001] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000441128800013 |
| 出版者 | SPRINGER HEIDELBERG |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/5061]  |
| 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, Peoples R China 2.Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Lisha,Chen, Yiqiang,Wang, Jindong,et al. OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition[J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS,2018,9(9):1577-1590. |
| APA | Hu, Lisha,Chen, Yiqiang,Wang, Jindong,Hu, Chunyu,&Jiang, Xinlong.(2018).OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition.INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS,9(9),1577-1590. |
| MLA | Hu, Lisha,et al."OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition".INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 9.9(2018):1577-1590. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。