Knowledge Commons of Institute of Automation,CAS
The Human Continuity Activity Semi-Supervised Recognizing Model for Multi-View IoT Network | |
Ruiwen Yuan; Wang JP(王军平)![]() | |
发表期刊 | IEEE Internet of Things Journal
![]() |
2023 | |
卷号 | 17期号:4页码:2031-2046 |
摘要 | With advances in spatial-temporal internet of things (IoT) technologies, human activity recognition (HAR) has played a major role in human safety and medical health. Recently, most works focus on activity deep feature extraction, offering promising alternatives to manually engineered features. However, how to extract the effective and distinguishable continuity activity features and meanwhile reduce the heavy dependence on labels still remains the key challenge for human activity recognition. This paper proposes the human continuity activity semi-supervised recognizing method in multi-view IoT network scenarios. Our innovation combines supervised activity feature extraction with unsupervised encoder-decoder modules, which can capture continuity activity features from sensor data streams. To be more specific, our work applies convolutional neural network (CNN) to capture the local dependence of sensor data and designs an encoder-decoder architecture to extract temporal features in an unsupervised manner. Then we fuse these two features to recognize activities and train them with manual labels, thereby refining the temporal feature extraction and training CNN module. Experiments on five public datasets demonstrate the exceptional performance of our proposed method, which can achieve a higher recognition accuracy on almost all the datasets and is more robust and adaptive among different datasets. |
收录类别 | SCIE |
是否为代表性论文 | 是 |
七大方向——子方向分类 | 机器学习 |
国重实验室规划方向分类 | 复杂系统建模与推演 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/51636 |
专题 | 多模态人工智能系统全国重点实验室_人工智能与机器学习(杨雪冰)-技术团队 |
通讯作者 | Ruiwen Yuan |
作者单位 | Institute of Automation, Research Center of Precision Sensing and Control, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Ruiwen Yuan,Wang JP. The Human Continuity Activity Semi-Supervised Recognizing Model for Multi-View IoT Network[J]. IEEE Internet of Things Journal,2023,17(4):2031-2046. |
APA | Ruiwen Yuan,&Wang JP.(2023).The Human Continuity Activity Semi-Supervised Recognizing Model for Multi-View IoT Network.IEEE Internet of Things Journal,17(4),2031-2046. |
MLA | Ruiwen Yuan,et al."The Human Continuity Activity Semi-Supervised Recognizing Model for Multi-View IoT Network".IEEE Internet of Things Journal 17.4(2023):2031-2046. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
The_Human_Continuity(1265KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
个性服务 |
推荐该条目 |
保存到收藏夹 |
查看访问统计 |
导出为Endnote文件 |
谷歌学术 |
谷歌学术中相似的文章 |
[Ruiwen Yuan]的文章 |
[Wang JP(王军平)]的文章 |
百度学术 |
百度学术中相似的文章 |
[Ruiwen Yuan]的文章 |
[Wang JP(王军平)]的文章 |
必应学术 |
必应学术中相似的文章 |
[Ruiwen Yuan]的文章 |
[Wang JP(王军平)]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
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。
修改评论