A Self-Supervised Human Activity Recognition Approach via Body Sensor Networks in Smart City

Author:

Zhou Yu1,Xie Chuanshi1,Sun Shilong2ORCID,Zhang Xiao3ORCID,Wang Yufan4

Affiliation:

1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

2. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China

3. Department of Computer Science, South-Central Minzu University, Wuhan, China

4. Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

Research Start-up Funds of South Central Minzu University

Shenzhen Fundamental Research Program

Fundamental Research Funds for the Central Universities, South-Central Minzu University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Continual Egocentric Activity Recognition With Foreseeable-Generalized Visual–IMU Representations;IEEE Sensors Journal;2024-04-15

2. Improving Human Activity Recognition Through Multisensor Data Fusion Techniques in Wireless Sensor Networks;2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI);2024-04-13

3. Energy-Efficient and Interpretable Multisensor Human Activity Recognition via Deep Fused Lasso Net;IEEE Transactions on Emerging Topics in Computational Intelligence;2024

4. Entropy and Memory Aware Active Transfer Learning in Smart Sensing Systems;IEEE Access;2024

5. Contrastive Learning Based Human Activity Recognition Using Body Sensors;2023 9th International Conference on Big Data Computing and Communications (BigCom);2023-08-04

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