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home/Knowledge Base/CODES/Classification of Hyperspectral Images/Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data

Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data

February 4, 2016

Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data
M. Fauvel, J. Chanussot, J.A. Benediktsson & A. Villa

Pattern Recognition
Volume: 46 , Issue: 3
Publication Year: 2013 , Page(s): 845-854

Tags:high dimensional datahigh dimensional discriminant analysishyperspectral imagingkernel methodsparsimonious Mahalanobis kernelSVM
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Categories
  • CODES
    • Anomaly
    • Change Detection
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Data fusion: Hyperspectral + Multispectral
    • Deep Learning
    • Denoising
    • Feature Extraction
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    • Graphs, Manifold
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    • Hyperspectral Super Resolution
    • Infrared
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    • Object Detection
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    • Registration
    • Sequences
    • Spectral Unmixing
    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Target Detection
    • Tensor
  • DATA

  Semisupervised Cross-Scale Graph Prototypical Network for Hyperspectral Image Classification

Parsimonious Gaussian Process Models for the Classification of Hyperspectral Remote Sensing Images  

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