Results 31 to 40 of about 3,590 (264)
Coherency Matrix Decomposition-Based Polarimetric Persistent Scatterer Interferometry [PDF]
, 2019 © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new ...
Mallorquí Franquet, Jordi Joan +1 more
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IEEE Access, 2019 Unsupervised polarimetric synthetic aperture radar (PolSAR) image classification is an important task in PolSAR automatic image analysis and interpretation.
Huanxin Zou +3 more
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Joint Polarimetric-Adjacent Features Based on LCSR for PolSAR Image Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Image classification is a critical and important application in PolSAR image interpretation. Finding a feature extraction method, which can effectively describe the characteristics of the target, is an important basis for image classification.
Xiao Wang +3 more
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Deep learning in remote sensing: a review [PDF]
, 2017 Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
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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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PolSAR Image Feature Extraction via Co-Regularized Graph Embedding
Remote Sensing, 2020 Dimensionality reduction (DR) methods based on graph embedding are widely used for feature extraction. For these methods, the weighted graph plays a vital role in the process of DR because it can characterize the data’s structure information.
Xiayuan Huang, Xiangli Nie, Hong Qiao
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Canadian Journal of Remote Sensing, 2023 Polarimetric synthetic aperture radar (PolSAR) images are classified mainly according to the backscattering information of ground objects. For regions with complex backscattering information, misclassification is easy to occur, which leads to challenges ...
Yan Duan +3 more
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Analytic Expressions for Stochastic Distances Between Relaxed Complex Wishart Distributions [PDF]
, 2013 The scaled complex Wishart distribution is a widely used model for multilook full polarimetric SAR data whose adequacy has been attested in the literature.
Cintra, Renato J. +2 more
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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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Egyptian Journal of Remote Sensing and Space Sciences, 2022 Although various deep neural networks such as convolutional neural networks (CNNs) have been suggested for classification of polarimetric synthetic aperture radar (PolSAR) images, but, they have several deficiencies.
Maryam Imani
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