Results 1 to 10 of about 2,015 (220)
Adversarial Reconstruction-Classification Networks for PolSAR Image Classification [PDF]
Remote Sensing, 2019 Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more widely used in recent years. It is well known that PolSAR image classification is a dense prediction problem. The recently proposed fully convolutional networks (
Yanqiao Chen +5 more
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Two-step discriminant analysis based multi-view polarimetric SAR image classification with high confidence [PDF]
Scientific Reports, 2022 Polarimetric synthetic aperture radar (PolSAR) image classification is a hot topic in remote sensing field. Although recently many deep learning methods such as convolutional based networks have provided great success in PolSAR image classification, but ...
Maryam Imani
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POLSAR Image Classification via Clustering-WAE Classification Model
IEEE Access, 2018 Considering the clustering algorithms could explore the label information automatically, this paper proposes a new method in terms of polarimetric synthetic aperture radar (POLSAR) image classification, which named a clustering-wishart-auto-encoder (WAE)
Wen Xie, Ziwei Xie, Feng Zhao, Bo Ren
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Unsupervised Classification of Polarimetric SAR Image Based on Geodesic Distance and Non-Gaussian Distribution Feature [PDF]
Sensors, 2021 Polarimetric synthetic aperture radar (PolSAR) image classification plays a significant role in PolSAR image interpretation. This letter presents a novel unsupervised classification method for PolSAR images based on the geodesic distance and K-Wishart ...
Junrong Qu +3 more
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Structure Label Matrix Completion for PolSAR Image Classification [PDF]
Remote Sensing, 2020 Terrain classification is a hot topic in polarimetric synthetic aperture radar (PolSAR) image interpretation that aims at assigning a label to every pixel and forms a label matrix for a PolSAR image.
Qian Wu +5 more
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Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks [PDF]
Sensors, 2018 Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image ...
Lei Wang +4 more
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DNN-Based PolSAR Image Classification on Noisy Labels
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Deep neural networks (DNNs) appear to be a solution for the classification of polarimetric synthetic aperture radar (PolSAR) data in that they outperform classical supervised classifiers under the condition of sufficient training samples. The design of a classifier is challenging because DNNs can easily overfit due to limited remote sensing training ...
Jun Ni +5 more
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Fisher Vectors for PolSAR Image Classification [PDF]
IEEE Geoscience and Remote Sensing Letters, 2017 In this letter, we study the application of the Fisher vector (FV) to the problem of pixelwise supervised classification of polarimetric synthetic aperture radar images. This is a challenging problem since information in those images is encoded as complex-valued covariance matrices. We observe that the real parts of these matrices preserve the positive
Javier Redolfi +2 more
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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
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Deep Curriculum Learning for PolSAR Image Classification
2022 International Conference on Machine Vision and Image Processing (MVIP), 2022 Following the great success of curriculum learning in the area of machine learning, a novel deep curriculum learning method proposed in this paper, entitled DCL, particularly for the classification of fully polarimetric synthetic aperture radar (PolSAR) data.
Mousavi, Hamidreza +2 more
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