YichuXu/MambaMoE

[Information Fusion 2025] MambaMoE: Mixture-of-Spectral-Spatial-Experts State Space Model for Hyperspectral Image Classification

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Emerging

This project helps classify different land covers or objects in satellite or aerial hyperspectral images. You provide raw hyperspectral image data (like '.mat' files) and it outputs a classification of what's in the image, such as different types of crops, urban areas, or water bodies. It's designed for remote sensing scientists, environmental analysts, or geographers who work with detailed spectral imagery.

Use this if you need to accurately identify and map land cover or specific materials from high-resolution hyperspectral satellite or airborne imagery.

Not ideal if you are working with standard RGB images or require general object detection rather than detailed spectral classification.

hyperspectral-imaging land-cover-mapping remote-sensing environmental-monitoring earth-observation
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 0 / 25

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Stars

33

Forks

Language

Python

License

MIT

Last pushed

Jan 18, 2026

Commits (30d)

0

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