Hyperspectral Image Classification With Re-Attention Agent Transformer and Multiscale Partial Convolution

Convolutional neural networks (CNNs) focus solely on extracting local features, lacking the ability to capture global spectral-spatial information. Meanwhile, Transformers effectively learn the overall distribution and mutual relationships of spectral features but overlook the extraction of local sp...

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Bibliographic Details
Main Authors:	Junding Sun, Hongyuan Zhang, Jianlong Wang, Haifeng Sima, Shuanggen Jin
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:	Attention mechanism convolutional neural network (CNN) feature fusion hyperspectral image classification transformer
Online Access:	https://ieeexplore.ieee.org/document/11104801/
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Hyperspectral Image Classification With Re-Attention Agent Transformer and Multiscale Partial Convolution

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