A New Parallel Dual-Channel Fully Convolutional Network Via Semi-Supervised FCM for PolSAR Image Classification

A New Parallel Dual-Channel Fully Convolutional Network Via Semi-Supervised FCM for PolSAR Image Classification

Convolutional neural network (CNN) has achieved remarkable success in polarimetric synthetic aperture radar (PolSAR) image classification. However, the PolSAR image classification is a pixelwise prediction assignment. The disadvantages of repeated calculation, memory occupation, and inadequate label...

Full description

Bibliographic Details
Main Authors: Feng Zhao, Min Tian, Wen Xie, Hanqiang Liu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Dilated FCN (DFCN)
dual-channel dilated fully convolutional network (DCDFCN)
fully convolutional network (FCN)
polarimetric synthetic aperture radar (PolSAR)
semi-supervised fuzzy c-means clustering (SSFCM)
Online Access:https://ieeexplore.ieee.org/document/9162444/

Internet

https://ieeexplore.ieee.org/document/9162444/

Similar Items