A Coarse-to-Fine Hierarchical Feature Learning for SAR Automatic Target Recognition With Limited Data-Reference-Cited by-同舟云学术

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A Coarse-to-Fine Hierarchical Feature Learning for SAR Automatic Target Recognition With Limited Data

Published:2024 Issue: Volume:17 Page:13646-13656
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Wen Yan¹^ORCID,Wang Xihao²^ORCID,Peng Lihe³^ORCID,Qiao Yu⁴

Affiliation:

1. School of Mechanical, Electrical Information, Chengdu Agricultural College, Chengdu, China

2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China

3. Suzhou Tongyuan Software & Control Technology Company, Suzhou, China

4. College of Computer Science, Chongqing University, Chongqing, China

Funder

2022 Industry-Education Integration Demonstration Project of Sichuan Province

Chengdu Agricultural College Institutional

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/4609443/10330207/10585317.pdf?arnumber=10585317

Reference47 articles.

1. A New Statistical-Based Kurtosis Wavelet Energy Feature for Texture Recognition of SAR Images

2. Automatic Target Recognition: State of the Art Survey

3. Ship recognition in high resolution SAR imagery based on feature selection

4. Gradient-based learning applied to document recognition

5. Densely Connected Convolutional Networks

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