Multi-frequency and multi-domain human activity recognition based on SFCW radar using deep learning

Deep learning and radar make it feasible to automatically recognize human activities in various lighting conditions, even occlusion case, which significantly promotes the application of activity recognition in the fields of security surveillance, health care, and so on. In this paper, an approach fo...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 444; S. 274 - 287
Hauptverfasser:	Jia, Yong, Guo, Yong, Wang, Gang, Song, Ruiyuan, Cui, Guolong, Zhong, Xiaoling
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 15.07.2021
Schlagworte:	Deep convolutional neural networks Human activity recognition Multi-frequency spectrograms Range maps SFCW radar Sparse autoencoder Deep convolutional neural networks Sparse autoencoder Human activity recognition Range maps Multi-frequency spectrograms SFCW radar
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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