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hannah-fathi / attention-unet-sentinel2-landcover-segmentation

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Deep learning-based semantic segmentation of Sentinel-2 multispectral imagery for agricultural land cover classification. The project uses a custom Attention U-Net with spectral indices (NDVI, NDWI, MNDWI, EVI, AWEI) and an end-to-end pipeline including auto-labeling, patch-based training, and GIS-ready inference.

computer-vision deep-learning agriculture geospatial gis pytorch remote-sensing image-segmentation semantic-segmentation earth-observation ndvi weakly-supervised-learning evi sentinel-2 awei ndwi multispectral land-cover-classification attention-unet mndwi
  • Updated Aug 21, 2026
  • Jupyter Notebook

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