Human Identification Based on Short-Time Radar Spectrograms Using Transformer Network-Reference-Cited by-同舟云学术

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Human Identification Based on Short-Time Radar Spectrograms Using Transformer Network

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:2021 CIE International Conference on Radar (Radar)
language:
Short-container-title:

Author:

Lang Yue¹,Yang Yang²,Zhou Yatong¹,Ji Haoran³,He Yuan⁴,Wang Qing⁵

Affiliation:

1. School of Electronics and Information Engineering, Hebei University of Technology,Tianjin,China

2. School of Electronical and Information Engineering, Tianjin University,Tianjin,China

3. Tianjin International Engineering Institute, Tianjin University,Tianjin,China

4. School of ICE, Beijing University of Posts and Telecommunications,Beijing,China

5. School of Electronics and Information Engineering, Tianjin University,Tianjin,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10027857/10027626/10028261.pdf?arnumber=10028261

Reference18 articles.

1. A Hybrid CNN–LSTM Network for the Classification of Human Activities Based on Micro-Doppler Radar

2. Attention is all you need;vaswani;Advances in neural information processing systems,2017

3. Multi-target human gait classification using LSTM recurrent neural networks applied to micro-Doppler

4. Segmented convolutional gated recurrent neural networks for human activity recognition in ultra-wideband radar

5. Long Short-Term Memory

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