RSEFormer: A Residual Squeeze-Excitation-Based Transformer for Pixelwise Hyperspectral Image Classification

RSEFormer: A Residual Squeeze-Excitation-Based Transformer for Pixelwise Hyperspectral Image Classification

Hyperspectral image (HSI) classification plays an essential role in remote sensing image processing. Deep learning methods, especially the transformer, has achieved great success in HSI classification. However, due to the limited existing labeled data of HSI, the relation between objects is irregula...

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Bibliographic Details
Main Authors: Yusen Liu, Hao Zhang, Fashuai Li, Fei Han, Yicheng Wang, Hao Pan, Boyu Liu, Guoliang Tang, Genghua Huang, Tingting He, Yuwei Chen
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Hyperspectral image (HSI) classification
residual network
squeeze-and-excitation module
vision transformer (ViT)
Online Access:https://ieeexplore.ieee.org/document/10962545/
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https://ieeexplore.ieee.org/document/10962545/

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