A hybrid convolution transformer for hyperspectral image classification

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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Bibliographic Details
Main Authors:	Tahir Arshad, Junping Zhang, Inam Ullah
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2024-12-01
Series:	European Journal of Remote Sensing
Subjects:	Convolutional neural network hyperspectral image classification vision transformer remote sensing data
Online Access:	https://www.tandfonline.com/doi/10.1080/22797254.2024.2330979
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