Stacked Sparse Autoencoder in PolSAR Data Classification Using Local Spatial Information.
IEEE Geoscience and Remote Sensing Letters（2016）
摘要
Terrain classification is an important topic in polarimetric synthetic aperture radar (PolSAR) image processing. Among various classification techniques, the stacked sparse autoencoder (SSAE) is a kind of deep learning method that can automatically learn useful features layer by layer in an unsupervised manner. However, the scattering measurements of individual pixels in PolSAR images are affected...
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关键词
Feature extraction,Training,Speckle,Cost function,Machine learning,Data mining,Scattering
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