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A hybrid convolution transformer for hyperspectral image classification

Hyperspectral images play a crucial role in remote sensing applications surveillance, environment and precision agriculture, containing abundant object information. However, they often face challenges such as limited labelled data and imbalanced classes. In recent years, convolutional neural network...

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Bibliografische gegevens
Hoofdauteurs: Tahir Arshad, Junping Zhang, Inam Ullah
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Taylor & Francis Group 2024-12-01
Reeks:European Journal of Remote Sensing
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Online toegang:https://www.tandfonline.com/doi/10.1080/22797254.2024.2330979
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