Fusing Transformers in a Tuning Fork Structure for Hyperspectral Image Classification Across Disjoint Samples

The 3-D swin transformer (3DST) and spatial–spectral transformer (SST) each excel in capturing distinct aspects of image information: the 3DST with hierarchical attention and window-based processing, and the SST with self-attention mechanisms for long-range dependencies. However, applying the...

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Principais autores:	Muhammad Ahmad, Muhammad Usama, Manuel Mazzara, Salvatore Distefano, Hamad Ahmed Altuwaijri, Silvia Liberata Ullo
格式:	Artigo
語言:	Inglês
出版:	IEEE 2024-01-01
叢編:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
主題:	3-D Swin Transformer (3DST) feature fusion hyperspectral image classification (HSIC) spatial–spectral features spatial–spectral transformer (SST)
在線閱讀:	https://ieeexplore.ieee.org/document/10685113/
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