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      SAR ATR Based on Convolutional Neural Network

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          Abstract

          This study presents a new method of Synthetic Aperture Radar (SAR) image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network’s ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 June 2016
          : 5
          : 3
          : 320-325
          Affiliations
          [1 ] ATR Key Laboratory, National University of Defense Technology, Changsha 410073, China
          Article
          42827ad78ec9432faf62335de14a0a82
          10.12000/JR16037

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

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