Chapter 27: Convolutional Neural Networks

Learning Objectives

• Implement Conv2d, BatchNorm, and activation layers with proper initialization
• Build residual blocks and skip connections for deep networks
• Implement the U-Net architecture from scratch for image-to-image tasks
• Implement DnCNN and DRUNet denoising networks for inverse problem applications