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Review on Supervised and Unsupervised Deep Learning Techniques for Hyperspectral Images Classification

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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) (AICV 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1377))

Abstract

Nowadays, the deep learning concept is used to solve Computer Vision’s many problems, as remote-sensing image classification. Hyperspectral image (HSI) classification is a major topic in the remote sensing field. Deep learning has different models used for hyperspectral image classification. These models are applied on numerous datasets and achieved excellent accuracy values. The existing HSI classification methods are categorized according to the features they use: pixel-wise methods, spectral-spatial methods, and deep learning methods. In this article, a comparison of different classification techniques is introduced.

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Author information

Authors and Affiliations

  1. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Mayar A. Shafaey, Mohammed A.-M. Salem, Maryam N. Al-Berry, Hala M. Ebied & Mohamed F. Tolba

  2. Faculty of Media Engineering and Technology, German University in Cairo, Cairo, Egypt

    Mohammed A.-M. Salem

Authors
  1. Mayar A. Shafaey
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  2. Mohammed A.-M. Salem
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  3. Maryam N. Al-Berry
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  4. Hala M. Ebied
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  5. Mohamed F. Tolba
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Editor information

Editors and Affiliations

  1. Information Technology Department, Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. School of Medicine, University of Missouri, Columbia, MO, USA

    Peter J. Tonellato

  4. ISAE-ENSMA, Futuroscope Chasseneuil Cedex, France

    Ladjel Bellatreche

  5. British University Vietnam, Hung Yen, Vietnam

    Sam Goundar

  6. Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt

    Ahmad Taher Azar

  7. NEST Research Group, ENSEM, Hassan II University of Casablanca, Casablanca, Morocco

    Essaid Sabir

  8. High National School for Computer Science and Systems Analysis (ENSIAS), Mohammed V University, Rabat, Morocco

    Driss Bouzidi

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Shafaey, M.A., Salem, M.AM., Al-Berry, M.N., Ebied, H.M., Tolba, M.F. (2021). Review on Supervised and Unsupervised Deep Learning Techniques for Hyperspectral Images Classification. In: Hassanien, A.E., et al. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). AICV 2021. Advances in Intelligent Systems and Computing, vol 1377. Springer, Cham. https://doi.org/10.1007/978-3-030-76346-6_7

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