Electromagnetic Scattering Feature (ESF) Module Embedded Network Based on ASC Model for Robust and Interpretable SAR ATR
Author:
Affiliation:
1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System and the College of Electronic Science and Technology, National University of Defense Technology, Changsha, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09896887.pdf?arnumber=9896887
Reference60 articles.
1. SAR Target Classification Based on Integration of ASC Parts Model and Deep Learning Algorithm
2. SAR Unlabeled Target Recognition Based on Updating CNN With Assistant Decision[-.2pc]
3. Contextual Region-Based Convolutional Neural Network with Multilayer Fusion for SAR Ship Detection
4. An Efficient and Robust Framework for SAR Target Recognition by Hierarchically Fusing Global and Local Features
5. Model-based classification of radar images
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