Terrain Classification of Polarimetric SAR Images Using Semi-supervised Spatial-channel Selective Kernel Network

Terrain Classification of Polarimetric SAR Images Using Semi-supervised Spatial-channel Selective Kernel Network

In this paper, a Spatial-Channel Selective Kernel Fully Convolutional Network (SCSKFCN) and a Semi-supervised Preselection-United Optimization (SPUO) method are proposed for polarimetric Synthetic Aperture Radar (SAR) image classification. Integrated with spatial-channel attention mechanism, SCSKFCN...

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Bibliographic Details
Main Authors: Ruichuan WANG, Yanfei WANG
Format: Article
Language:English
Published: China Science Publishing & Media Ltd. (CSPM) 2021-08-01
Series:Leida xuebao
Subjects:
terrain classification of polsar images
fully convolutional network
attention mechanism
semi-supervised learning
spatial-channel selective kernel network (scskcn)
Online Access:https://radars.ac.cn/cn/article/doi/10.12000/JR21080

Internet

https://radars.ac.cn/cn/article/doi/10.12000/JR21080

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