2 citations · 2 across the 2 of their papers we have counts for
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EnergyFormer: Energy Attention with Fourier Embedding for Hyperspectral Image Classification
Saad Sohail, Muhammad Usama, Usman Ghous +3
Hyperspectral imaging (HSI) provides rich spectral-spatial information across hundreds of contiguous bands, enabling precise material discrimination in applications such as environ…
Hybrid State-Space and GRU-based Graph Tokenization Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Muhammad Usama +4
Hyperspectral image (HSI) classification plays a pivotal role in domains such as environmental monitoring, agriculture, and urban planning. However, it faces significant challenges…
DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification
Muhammad Ahmad, Manuel Mazzara, Salvatore Distefano +2
Hyperspectral image classification (HSIC) has gained significant attention because of its potential in analyzing high-dimensional data with rich spectral and spatial information. I…
Transformer-Driven Active Transfer Learning for Cross-Hyperspectral Image Classification
Muhammad Ahmad, Francesco Mauro, Manuel Mazzara +3
Hyperspectral image (HSI) classification presents inherent challenges due to high spectral dimensionality, significant domain shifts, and limited availability of labeled data. To a…
Multi-head Spatial-Spectral Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Muhammad Usama +3
Spatial-Spectral Mamba (SSM) improves computational efficiency and captures long-range dependencies, addressing Transformer limitations. However, traditional Mamba models overlook…