Energy-Efficient and Interpretable Multisensor Human Activity Recognition via Deep Fused Lasso Net-Reference-Cited by-同舟云学术

Energy-Efficient and Interpretable Multisensor Human Activity Recognition via Deep Fused Lasso Net

Published:2024 Issue: Volume: Page:1-13
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Zhou Yu¹^ORCID,Xie Jingtao¹,Zhang Xiao²^ORCID,Wu Wenhui³^ORCID,Kwong Sam⁴^ORCID

Affiliation:

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

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

3. College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China

4. Department of Computing and Decision Science, Lingnan University, Hong Kong

Funder

Guangdong Basic and Applied Basic Research Foundation

Shenzhen Fundamental Research Program

Shenzhen Science and Technology Program

National Natural Science Foundation of China

Fund for Academic Innovation Teams and Research Platform of South-Central Minzu University

Knowledge Innovation Program of Wuhan-Basic Research

Research Start-up Funds of South-Central Minzu University

Spring Sunshine Program of Ministry of Education of the People's Republic of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

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