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home/Knowledge Base/CODES/Hyperspectral/Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

May 28, 2020

Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)

Behnood Rasti, Danfeng Hong, Renlong Hang, Pedram Ghamisi, Xudong Kang, Jocelyn Chanussot, And Jon Atli Benediktsson

IEEE Geoscience and Remote Sensing Magazine
DOI: 10.1109/MGRS.2020.2979764
Publication Year: 2020

 

Tags:feature extractionhyperspectral
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1 .pdf 5.97 MB 2020_IEEE_GRSM_feature_extraction
2 .rar 77.66 MB HyFTech-Hyperspectral-Shallow-Deep-Feature-Extraction-Toolbox-master
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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
    • Graphs
    • Graphs, Manifold
    • Hyperspectral
    • Hyperspectral remote sensing
    • Hyperspectral Super Resolution
    • Infrared
    • Machine Learning in Remote Sensing
    • Multi-modal
    • Object Detection
    • Pansharpening
    • Registration
    • Sequences
    • Spectral Unmixing
    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Target Detection
    • Tensor
  • DATA

  Few-shot Learning with Class-Covariance Metric for Hyperspectral Image Classification

Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing  

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