• Electronics Optics & Control
  • Vol. 27, Issue 10, 37 (2020)
REN Shuoliang, SUO Jidong, and TONG Yu
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2020.10.008 Cite this Article
    REN Shuoliang, SUO Jidong, TONG Yu. SAR Target Recognition Based on Convolution Neural Network and Transfer Learning[J]. Electronics Optics & Control, 2020, 27(10): 37 Copy Citation Text show less

    Abstract

    Aiming at the problems of low accuracy and long running time of CNN in SAR target recognition, a new method of transfering VGG16 is proposed based on the combination of transfer learning with convolution neural network VGG16 structure.Firstly, the target features are extracted by fine-tuning the pre-training model of transfering VGG16 for the SAR target in the MSTAR dataset.Then the feature is classified and recognized by Softmax classifier.Experiments show that:The SAR target recognition rate of the transfering VGG16 is increased to 94.4%, compared with 86.2% and 90.8% of the existing VGG16 algorithm and the transfering LENET method.
    REN Shuoliang, SUO Jidong, TONG Yu. SAR Target Recognition Based on Convolution Neural Network and Transfer Learning[J]. Electronics Optics & Control, 2020, 27(10): 37
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