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Articles | Volume 3
Articles | Volume 3
Abstr. Int. Cartogr. Assoc., 3, 189, 2021
https://doi.org/10.5194/ica-abs-3-189-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Abstr. Int. Cartogr. Assoc., 3, 189, 2021
https://doi.org/10.5194/ica-abs-3-189-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 3

  13 Dec 2021

13 Dec 2021

Computationally efficient sequential feature extraction for single hyperspectral remote sensing image classification

Andong Ma and Anthony M. Filippi Andong Ma and Anthony M. Filippi
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  • Department of Geography, College of Geosciences, Texas A&M University, College Station, TX, 77843, USA

Keywords: Hyperspectral remote sensing, Classification, Recurrent neural networks, Deep learning

How to cite. Ma, A. and Filippi, A. M.: Computationally efficient sequential feature extraction for single hyperspectral remote sensing image classification, Abstr. Int. Cartogr. Assoc., 3, 189, https://doi.org/10.5194/ica-abs-3-189-2021, 2021.
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