Semantic Segmentation of Aerial Imagery Using U-Net

This course demonstrates preprocessing aerial satellite imagery and pixel-wise masks for six land-cover classes, then training a U-Net and making segmentation predictions. It covers handling varied image sizes, extracting patches, encoding labels, and visualizing results.