10 papers
Cosine-Normalized Attention for Hyperspectral Image Classification
Muhammad Ahmad, Manuel Mazzara
Transformer-based methods have improved hyperspectral image classification (HSIC) by modeling long-range spatial-spectral dependencies; however, their attention mechanisms typicall…
3D Fourier-based Global Feature Extraction for Hyperspectral Image Classification
Muhammad Ahmad
Hyperspectral image classification (HSIC) has been significantly advanced by deep learning methods that exploit rich spatial-spectral correlations. However, existing approaches sti…
Dynamic Memory Transformer for Hyperspectral Image Classification
Muhammad Ahmad
Hyperspectral image (HSI) classification (HSIC) requires effective modeling of complex spatial-spectral dependencies under limited labeled data and high dimensionality. While trans…
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…
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…