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cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image Classification

Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Adil Mehmood Khan +6

Recent advancements in transformers, specifically self-attention mechanisms, have significantly improved hyperspectral image (HSI) classification. However, these models often suffe…

cs.CV2024

WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification

Muhammad Ahmad, Muhammad Usama, Manuel Mazzara +1

Hyperspectral Imaging (HSI) has proven to be a powerful tool for capturing detailed spectral and spatial information across diverse applications. Despite the advancements in Deep L…

cs.CV2024

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…

cs.CV2024

Transformers Fusion across Disjoint Samples for Hyperspectral Image Classification

Muhammad Ahmad, Manuel Mazzara, Salvatore Distifano

3D Swin Transformer (3D-ST) known for its hierarchical attention and window-based processing, excels in capturing intricate spatial relationships within images. Spatial-spectral Tr…