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home/Knowledge Base/CODES/Hyperspectral/Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects

Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects

March 30, 2022

Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects
Muhammad Ahmad, Sidrah Shabbir, Swalpa Kumar Roy, Danfeng Hong, Xin Wu, Jing Yao, Adil Mehmood Khan, Manuel Mazzara, Salvatore Distefano, and Jocelyn Chanussot.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
vol. 15, pp. 968-999, 2022
DOI: 10.1109/JSTARS.2021.3133021

Article Link: https://ieeexplore.ieee.org/document/9645266
Github code repository: https://github.com/AnkurDeria/HSI-Traditional-to-Deep-Models
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  • Machine Learning in Pansharpening: A Benchmark, From Shallow to Deep Networks
  • Multigraph-Based Low-Rank Tensor Approximation for Hyperspectral Image Restoration
  • Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution

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  • CODES
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  Hyperspectral Imagery Classification via Random Multi-Graphs Ensemble Learning

Graph Convolutional Networks for Hyperspectral Image Classification  

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