Results 11 to 20 of about 12,268,087 (190)

PolSAR Image Classification Based on Multi-Modal Contrastive Fully Convolutional Network

Remote Sensing
Deep neural networks have achieved remarkable results in the field of polarimetric synthetic aperture radar (PolSAR) image classification. However, PolSAR is affected by speckle imaging, resulting in PolSAR images usually containing a large amount of ...
Wenqiang Hua, Yi Wang, Sijia Yang, Xiaomin Jin   +3 more
doaj   +4 more sources

Fuzzy Superpixels Based Semi-Supervised Similarity-Constrained CNN for PolSAR Image Classification [PDF]

Remote Sensing, 2020
Recently, deep learning has been highly successful in image classification. Labeling the PolSAR data, however, is time-consuming and laborious and in response semi-supervised deep learning has been increasingly investigated in PolSAR image classification.
Yuwei Guo, Zhuangzhuang Sun, Rong Qu, Licheng Jiao, Fang Liu, Xiangrong Zhang   +5 more
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A Novel Deep Fully Convolutional Network for PolSAR Image Classification

Remote Sensing, 2018
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular in recent years. As we all know, PolSAR image classification is actually a dense prediction problem.
Yangyang Li, Yanqiao Chen, Guangyuan Liu, Licheng Jiao   +3 more
doaj   +2 more sources

PolSAR Image Classification Based on Statistical Distribution and MRF [PDF]

Remote Sensing, 2020
Classification is an important topic in synthetic aperture radar (SAR) image processing and interpretation. Because of speckle and imaging geometrical distortions, land cover mapping is always a challenging task especially in complex landscapes.
Junjun Yin 0001, Xiyun Liu, Jian Yang 0011, Chih-Yuan Chu 0002, Yang-Lang Chang   +4 more
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PolSAR Image Classification with Lightweight 3D Convolutional Networks [PDF]

Remote Sensing, 2020
Convolutional neural networks (CNNs) have become the state-of-the-art in optical image processing. Recently, CNNs have been used in polarimetric synthetic aperture radar (PolSAR) image classification and obtained promising results. Unlike optical images, the unique phase information of PolSAR data expresses the structure information of objects.
Hongwei Dong, Lamei Zhang, Bin Zou 0001
openaire   +4 more sources

A New Architecture of a Complex-Valued Convolutional Neural Network for PolSAR Image Classification

Remote Sensing, 2023
Polarimetric synthetic aperture radar (PolSAR) image classification has been an important area of research due to its wide range of applications. Traditional machine learning methods were insufficient in achieving satisfactory results before the advent ...
Yihui Ren, Wen Jiang, Ying Liu
doaj   +2 more sources

Complex-Valued Multi-Scale Fully Convolutional Network with Stacked-Dilated Convolution for PolSAR Image Classification

Remote Sensing, 2022
Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As a variant of the Convolutional Neural Network (CNN), the Fully Convolutional Network (FCN), which is ...
Wen Xie, Licheng Jiao, Wenqiang Hua
doaj   +2 more sources

Unsupervised PolSAR Image Classification Based on Superpixel Pseudo-Labels and a Similarity-Matching Network

Remote Sensing
Supervised polarimetric synthetic aperture radar (PolSAR) image classification demands a large amount of precisely labeled data. However, such data are difficult to obtain.
Lei Wang, Lingmu Peng, Rong Gui, Hanyu Hong, Shenghui Zhu   +4 more
doaj   +2 more sources

PolSAR image classification based on Laplacian Eigenmaps and superpixels [PDF]

EURASIP Journal on Wireless Communications and Networking, 2017
Abstract This paper proposes a method of polarimetric synthetic aperture radar (PolSAR) image classification using improved superpixel segmentation and manifold learning. Firstly, a 27-dimension polarimetric feature space is extracted by simple arithmetic operations of polarimetric parameters and polarimetric target decomposition.
Haijiang Wang 0001, Jinghong Han, Yangyang Deng   +2 more
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Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification

Remote Sensing
Superpixel segmentation has been widely used in the field of computer vision. The generations of PolSAR superpixels have also been widely studied for their feasibility and high efficiency. The initial numbers of PolSAR superpixels are usually designed manually by experience, which has a significant impact on the final performance of superpixel ...
Boce Chu, Mengxuan Zhang 0003, Kun Ma 0003, Long Liu 0004, Junwei Wan, Jinyong Chen, Jie Chen 0009, Hongcheng Zeng 0001   +7 more
openaire   +4 more sources