Human Activity Recognition Using Self-powered Sensors Based on Multilayer Bi-directional Long Short-Term Memory Networks-Reference-Cited by-同舟云学术

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Human Activity Recognition Using Self-powered Sensors Based on Multilayer Bi-directional Long Short-Term Memory Networks

Published:2022 Issue: Volume: Page:1-1
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Su Jian¹^ORCID,Liao Zhenlong¹,Sheng Zhengguo²^ORCID,Liu Alex X.³^ORCID,Singh Dilbag⁴,Lee Heung-No⁴^ORCID

Affiliation:

1. School of Computer and Software, Nanjing University of Information Science and Technology, Jiangsu, China

2. Department of Engineering and Design, University of Sussex, Brighton, U. K

3. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

4. School of Electrical Engineering and Computer Science, Gwangju Institure of Science and Technology, Gwangju, South Korea

Funder

National Natural Science Foundation of China

National Research Foundation of Korea

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/4427201/09851603.pdf?arnumber=9851603

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2. ASMGCN: Attention-Based Semantic-Guided Multistream Graph Convolution Network for Skeleton Action Recognition;IEEE Sensors Journal;2024-06-15

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