Improving Semantic Segmentation - U-Net Performance via Ensemble of Multiple Trained Networks

This course demonstrates how to improve multiclass semantic segmentation by independently training U-Net models with ResNet34, Inception V3, and VGG16 backbones, then combining their predictions through a weighted ensemble. It covers preprocessing, model loading, ensemble evaluation, and visualization of segmentation results.