Land Cover Segmentation from Satellite Imagery Using U-Net with Custom Loss and Morphological Postprocessing
This project designs and implements a semantic segmentation pipeline using a modified U-Net architecture from scratch for pixel-level classification of satellite images and demonstrates a full end-to-end pipeline from model design to web deployment and sets a foundation for scalable geospatial AI applications tailored...