Multiscenario Open-Set Gait Recognition Based on Radar Micro-Doppler Signatures-Reference-Cited by-同舟云学术

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Multiscenario Open-Set Gait Recognition Based on Radar Micro-Doppler Signatures

Published:2022 Issue: Volume:71 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Yang Yang¹^ORCID,Ge Yanyan¹^ORCID,Li Beichen¹^ORCID,Wang Qing¹^ORCID,Lang Yue²^ORCID,Li Kaiming³^ORCID

Affiliation:

1. School of Electrical and Information Engineering, Tianjin University, Tianjin, China

2. School of Electric and Information Engineering, Hebei University of Technology, Beichen, China

3. Information and Navigation College, Air Force Engineering University, Xi’an, China

Funder

National Natural Science Foundation of China

Science and Technology Project of the Hebei Education Department

Natural Science Foundation of Shaanxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09918048.pdf?arnumber=9918048

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1. Human Gait phases recognition based on multi-source data fusion and BILSTM attention neural network;Measurement;2024-10

2. Few-Shot Radar Jamming Recognition Network via Complete Information Mining;IEEE Transactions on Aerospace and Electronic Systems;2024-06

3. mDS-PCGR: A Bimodal Gait Recognition Framework With the Fusion of 4-D Radar Point Cloud Sequences and Micro-Doppler Signatures;IEEE Sensors Journal;2024-03-15

4. Real-Time Fall Recognition Using a Lightweight Convolution Neural Network Based on Millimeter-Wave Radar;IEEE Sensors Journal;2024-03-01

5. Quantitative Measurement of Parkinson’s Disease Gait Based on the Rehabilitation Monitoring Robot;IEEE Transactions on Instrumentation and Measurement;2024

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