Welcome to the Image Regression exercises. In this part of the course, we will explore how to use deep learning to denoise images, with examples of widely used algorithm for both supervised and unsupervised denoising. We will also explore the difference between unstructured and structured noise, or between UNet (which you are familiar with by now) and VAE architectures (see COSDD exercise)!
Finally, we have bonus exercises for those wanted to explore more denoising algorithms or image splitting!
Please run the setup script to create the environment for these exercises and download data.
source setup.shWhen you are ready to start the exercise, make sure you are in the 02_regression environment and then run jupyter lab.
mamba activate 02_regression
jupyter lab