Dust-Storm Image Segmentation with VGG16 U-Net - Binary Segmentation

Learn to build a VGG16-U-Net model for binary segmentation of dust storms in satellite imagery in this comprehensive 36-minute tutorial. Follow a step-by-step guide to create a deep learning model that effectively separates storm plumes from background terrain using TensorFlow 2. Master essential techniques including building the U-Net VGG16 architecture from scratch, creating an efficient data preprocessing pipeline, training the model on a specialized dust storm segmentation dataset, and performing inference on test images. The tutorial covers the complete workflow from installation through model deployment with practical code examples. Access the companion code through the provided link and explore related computer vision tutorials on image segmentation and visual language models through the instructor's blog and playlists.