View-spatial-attention Augmentation on Multi-view Micro-Doppler Spectra for Hidden Human Activity Recognition
Author:
Affiliation:
1. Fourth Military Medical University,School of Biomedical Engineering,Xi’an,China,710032
2. Chengdu University of Technology,School of Mechanical and Electrical Engineering,Chengdu,China,610059
Funder
National Natural Science Foundation of China
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10616250/10617814/10618477.pdf?arnumber=10618477
Reference13 articles.
1. Personnel recognition based on multistatic micro‐Doppler and singular value decomposition features
2. Aspect angle dependence and multistatic data fusion for micro‐Doppler classification of armed/unarmed personnel
3. Classification of Unarmed/Armed Personnel Using the NetRAD Multistatic Radar for Micro-Doppler and Singular Value Decomposition Features
4. Centroid features for classification of armed/unarmed multiple personnel using multistatic human micro‐Doppler
5. Personnel Recognition and Gait Classification Based on Multistatic Micro-Doppler Signatures Using Deep Convolutional Neural Networks
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