Multiscale Residual Attention Network for Distinguishing Stationary Humans and Common Animals Under Through-Wall Condition Using Ultra-Wideband Radar

Distinguishing between humans and common animals through a wall is necessary for facilitating successful rescue of survivors and enhancing the confidence of rescuers in post-disaster search and rescue operations. However, few existing solutions are available with only dogs considered in this scenari...

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Autores principales:	Yangyang Ma, Fugui Qi, Pengfei Wang, Fulai Liang, Hao Lv, Xiao Yu, Zhao Li, Huijun Xue, Jianqi Wang, Yang Zhang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2020-01-01
Colección:	IEEE Access
Materias:	Convolutional neural network (CNN) distinguishing between stationary humans and common animals post-disaster rescue residual attention learning mechanism ultra-wideband (UWB) radar
Acceso en línea:	https://ieeexplore.ieee.org/document/9133087/
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