Joint sparse representation of complementary components in SAR images for robust target recognition-Reference-Cited by-同舟云学术

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Joint sparse representation of complementary components in SAR images for robust target recognition

Published:2018-07-19 Issue:7 Volume:33 Page:882-896
ISSN:0920-5071
Container-title:Journal of Electromagnetic Waves and Applications
language:en
Short-container-title:Journal of Electromagnetic Waves and Applications

Author:

Miao Shuguang¹²³,Liu Xiaowen¹³

Affiliation:

1. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, People's Republic of China

2. School of Physics and Electronic Information, Huaibei Normal University, Huaibei, People's Republic of China

3. IOT Perception Mine Research Center, China University of Mining and Technology, Xuzhou, People's Republic of China

Funder

National Key Basic Research Program of China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,General Physics and Astronomy,Electronic, Optical and Magnetic Materials

Link

https://www.tandfonline.com/doi/pdf/10.1080/09205071.2018.1496038

Reference31 articles.

1. Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review

2. Target detection in synthetic aperture radar imagery: a state-of-the-art survey

3. New Discrimination Features for SAR Automatic Target Recognition

4. Automatic target recognition of synthetic aperture radar (SAR) images based on optimal selection of Zernike moments features

5. Automatic Target Recognition of Military Vehicles With Krawtchouk Moments

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3. Target recognition of SAR images using fused deep feature by multiset canonical correlations analysis;Optik;2020-10

4. Target classification of SAR images using nonlinear correlation information entropy;Journal of Applied Remote Sensing;2020-09-30

5. Two-stage sparse representation of NSCT features with application to SAR target classification;Journal of Electromagnetic Waves and Applications;2020-09-09

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