Results 101 to 110 of about 2,015 (220)
Independent component analysis within polarimetric incoherent target decomposition
, 2013 International audienceThis paper represents a part of our efforts to generalize polarimetric incoherent target decomposition to the level of BSS techniques by introducing the ICA method instead of the conventional eigenvector decomposition.
Besic, Nikola +5 more
core +2 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHigh-quality labeled samples of polarimetric synthetic aperture radar (PolSAR) images are relatively scarce. Therefore, achieving optimal classification performance with limited labeled samples has become a significant challenge in PolSAR image ...
Nana Jiang +4 more
doaj +1 more source
Superpixel-Based Classification Using K Distribution and Spatial Context for Polarimetric SAR Images
Remote Sensing, 2016 Classification techniques play an important role in the analysis of polarimetric synthetic aperture radar (PolSAR) images. PolSAR image classification is widely used in the fields of information extraction and scene interpretation or is performed as a ...
Qiao Xu +3 more
doaj +1 more source
Visualization of Skewed Data: A Tool in R [PDF]
, 2014 In this work we present a visualization tool specifically tailored to deal with skewed data. The technique is based upon the use of two types of notched boxplots (the usual one, and one which is tuned for the skewness of the data), the violin plot, the ...
Frery, A. C. +2 more
core +2 more sources
A Broad Class of Discrete-Time Hypercomplex-Valued Hopfield Neural Networks
, 2019 In this paper, we address the stability of a broad class of discrete-time hypercomplex-valued Hopfield-type neural networks. To ensure the neural networks belonging to this class always settle down at a stationary state, we introduce novel hypercomplex ...
de Castro, Fidelis Zanetti +1 more
core +1 more source
Context-Based Max-Margin for PolSAR Image Classification
IEEE Access, 2017 Context-based method for classification has been successfully applied in image. However, most of these classifiers work in stages. This paper presents a novel discriminative model named context-based max-margin to perform the task of classification for polarimetric synthetic aperture radar (PolSAR) images.
Shuyin Zhang +5 more
openaire +2 more sources
Multichannel semi-supervised active learning for PolSAR image classification
International Journal of Applied Earth Observations and GeoinformationDeep neural networks have recently been extensively utilized for Polarimetric synthetic aperture radar (PolSAR) image classification. However, this heavily relies on extensive labeled data which is both costly and labor-intensive. To lower the collection
Wenqiang Hua +4 more
doaj +1 more source
PolSAR-SFCGN: An End-to-End PolSAR Superpixel Fully Convolutional Generation Network
Remote SensingPolarimetric 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
doaj +1 more source
A 3-D Convolutional Vision Transformer for PolSAR Image Classification and Change Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe scattering properties of targets in polarimetric synthetic aperture radar (PolSAR) images are directly influenced by the targets' orientations, as the scattering properties from the same target with different orientations can be very different.
Lei Wang +5 more
doaj +1 more source
Semi-Supervised Classification of PolSAR Images Based on Co-Training of CNN and SVM with Limited Labeled Samples. [PDF]
Sensors (Basel), 2023 Zhao M, Cheng Y, Qin X, Yu W, Wang P.
europepmc +1 more source