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home/Knowledge Base/CODES/Spectral Unmixing/MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing

MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing

January 31, 2022

MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing
B. Rasti, B. Koirala, P. Scheunders and J. Chanussot

IEEE Transactions on Geoscience and Remote Sensing
DOI: 10.1109/TGRS.2022.3146904.

codes : https://github.com/BehnoodRasti/MiSiCNet

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1 .pdf 22.12 MB MiSiCNet_Minimum_Simplex_Convolutional_Network_for_Deep_Hyperspectral_Unmixing
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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
    • Hyperspectral
    • Hyperspectral remote sensing
    • Hyperspectral Super Resolution
    • Infrared
    • Machine Learning in Remote Sensing
    • Multi-modal
    • Object Detection
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    • Registration
    • Sequences
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    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Target Detection
    • Tensor
    • Transformer
  • DATA

  More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

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