SSSAT-Net: Spectral-Spatial Self-Attention-Based Transformer Network for hyperspectral image classification

doi:10.1016/j.optlaseng.2025.109154

SSSAT-Net: Spectral-Spatial Self-Attention-Based Transformer Network for hyperspectral image classification

2025-06-07

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DOI：10.1016/j.optlaseng.2025.109154

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• Spectral attention module is designed for feature extraction and channel selection. • Manhattan Distance is used to investigate central and neighboring feature vectors. • Multi-Scale Convolutional Information Fusion Module is introduced. • Feature Learning Module is crafted for efficient spectral-spatial feature learning. • Transformer is employed to capture global attention refined features.

SSSAT-Net: Spectral-Spatial Self-Attention-Based Transformer Network for hyperspectral image classification

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