.png){kind=icon}
返回
Cross-position activity recognition with stratified transfer learning
.png){kind=icon}
OA
AI
DOI：10.1016/j.pmcj.2019.04.004.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Human activity recognition (HAR) aims to recognize the activities of daily living by utilizing the sensors attached to different body parts. HAR relies on the machine learning models trained using sufficient activity data. However, when the labels from a certain body position (i.e. target domain) are missing, how to leverage the data from other positions (i.e. source domain) to help recognize the activities of this position? This problem can be divided into two steps. Firstly, when there are several source domains available, it is often difficult to select the most similar source domain to the target domain. Secondly, with the selected source domain, we need to perform accurate knowledge transfer between domains in order to recognize the activities on the target domain. Existing methods only learn the global distance between domains while ignoring the local property. In this paper, we propose a Stratified Transfer Learning (STL) framework to perform both source domain selection and activity transfer. STL is based on our proposed Stratified distance to capture the local property of domains. STL consists of two components: 1) Stratified Domain Selection (STL-SDS), which can select the most similar source domain to the target domain; and 2) Stratified Activity Transfer (STL-SAT), which is able to perform accurate knowledge transfer. Extensive experiments on three public activity recognition datasets demonstrate the superiority of STL. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Activity recognition
Transfer learning
Domain adaptation
Pervasive computing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
1.5K
被引数:
2.2K
机构
引用论文
Autologous graft-versus-host disease: harnessing anti-tumor immunity through impaired self-tolerance
.png){kind=icon}
PREAI
分享收藏分享收藏分享收藏A Tutorial on Human Activity Recognition Using Body-Worn Inertial Sensors使用身体佩戴的惯性传感器进行人体活动识别的教程
PREAI
分享收藏分享收藏
查看更多内容