Multilevel Scattering Center and Deep Feature Fusion Learning Framework for SAR Target Recognition
Author:
Affiliation:
1. Key Laboratory of Information Fusion Technology, Ministry of Education, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Funder
National Natural Science Foundation of China
Natural Science Basic Research Plan in Shaanxi Province 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/ielx7/36/9633014/09773339.pdf?arnumber=9773339
Reference58 articles.
1. Feature Extraction Using Attributed Scattering Center Models for Model-Based Automatic Target Recognition (ATR)
2. Attributed Scattering Center Extraction With Genetic Algorithm
3. FEC: A Feature Fusion Framework for SAR Target Recognition Based on Electromagnetic Scattering Features and Deep CNN Features
4. An Efficient and Robust Framework for SAR Target Recognition by Hierarchically Fusing Global and Local Features
5. A parametric model for synthetic aperture radar measurements
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