Research on Ground Object Classification Detection Method of Heterologous SAR Image Based on Transfer Learning

被引:0
|
作者
Wu, Shengna [1 ]
Wang, Ke [1 ]
Ouyang, Yiwen [1 ]
机构
[1] Henan Univ Technol, Sch Informat Sci & Engn, Zhengzhou, Henan, Peoples R China
关键词
deep learning; transfer learning; SAR image; classification detection;
D O I
10.1109/itaic.2019.8785852
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the classification detection of Synthetic Aperture Radar (SAR) images, there are SAR images acquired from different radars. For the problem of ground objects classification detection of less-label heterogeneous SAR images,this paper uses the Convolutional Neural Network (CNN) based on transfer learning to train a pre-trained network with fewer labels.To fine-tune the network, we can realize the ground object classification detection of heterogeneous SAR images. The effectiveness of the proposed method is verified by experiments.
引用
收藏
页码:1496 / 1499
页数:4
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