PolSAR-SFCGN: An End-to-End PolSAR Superpixel Fully Convolutional Generation Network
Polarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. The impressive superpixel generation approaches can improve the efficiency of the subsequent classification task and restrain
Mengxuan Zhang +6 more
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Perceptually Optimal Color Representation of Fully Polarimetric SAR Imagery. [PDF]
Koukiou G.
europepmc +1 more source
Gaofen-3 PolSAR Image Classification via XGBoost and Polarimetric Spatial Information. [PDF]
Dong H, Xu X, Wang L, Pu F.
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Polarimetric SAR Speckle Filtering Using a Nonlocal Weighted LMMSE Filter. [PDF]
Shen Y, Ma X, Zhu S, Xu J.
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Land Use and Land Cover Classification Meets Deep Learning: A Review. [PDF]
Zhao S, Tu K, Ye S, Tang H, Hu Y, Xie C.
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Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory. [PDF]
Peng D, Zhang H, Guo W, Yang W.
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Survey of Transverse Range Fire Scars in 10 Years of UAVSAR Polarimetry. [PDF]
Parker J, Donnellan A, Glasscoe M.
europepmc +1 more source
Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method. [PDF]
Zhu L, Ma X, Wu P, Xu J.
europepmc +1 more source
PolSAR image classification using shallow to deep feature fusion network with complex valued attention. [PDF]
Alkhatib MQ +4 more
europepmc +1 more source
Unsupervised Classification of Polarimetric SAR Image Based on Geodesic Distance and Non-Gaussian Distribution Feature. [PDF]
Qu J, Qiu X, Ding C, Lei B.
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