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

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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Bibliographic Details
Main Authors: Yangyang Ma, Fugui Qi, Pengfei Wang, Fulai Liang, Hao Lv, Xiao Yu, Zhao Li, Huijun Xue, Jianqi Wang, Yang Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Convolutional neural network (CNN)
distinguishing between stationary humans and common animals
post-disaster rescue
residual attention learning mechanism
ultra-wideband (UWB) radar
Online Access:https://ieeexplore.ieee.org/document/9133087/

Internet

https://ieeexplore.ieee.org/document/9133087/

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