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In this paper, we propose a new deep artificial neural network architecture for synthetic aperture radar target recognition codenamed DeepSAR-Net. Unlike most existing methods, this approach can learn discriminative features directly from the training data instead of requiring pre-specification or pre-selection by a human designer. Furthermore, our method is adaptable, and it is learning to recognize...
In this paper, an unsupervised classification for compact polarimetry SAR (C-PolSAR) image is proposed by combining the H/α decomposition with the Wishart classifier. Firstly, H/α decomposition method is applied to the compact polarimetry (CP) data. By analyzing the different (H, a) values corresponding to the three compact polarimetry mode: the π/4, CL, and CC modes, we find that only in the CC mode,...
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