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home/Knowledge Base/CODES/Hyperspectral/Spectralformer: Rethinking hyperspectral image classification with transformers

Spectralformer: Rethinking hyperspectral image classification with transformers

December 17, 2021

Spectralformer: Rethinking hyperspectral image classification with transformers
Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot.

IEEE Transactions on Geoscience and Remote Sensing (TGRS)
2022, DOI: 10.1109/TGRS.2021.3130716

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1 .pdf 14.99 MB SpectralFormer_Rethinking_Hyperspectral_Image_Classification_with_Transformers
2 .zip 13.85 MB IEEE_TGRS_SpectralFormer-main
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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
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    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Target Detection
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  • DATA

  UIU-Net: U-Net in U-Net for Infrared Small Object Detection

Semisupervised Cross-Scale Graph Prototypical Network for Hyperspectral Image Classification  

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Mail : Jocelyn Chanussot

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