U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger, Philipp Fischer, Thomas Brox · 2015

U-Net. Encoder-decoder with skip connections that became the default architecture for medical imaging and any dense-prediction task on small datasets.

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What you'll get

Outline: a plain-English breakdown of the paper's core idea, prerequisites, and the concepts you'll need to implement it.
Exercises: five to ten hands-on tasks, each with a concept card, a prompt, a starter code stub, and a collapsible reference solution.
Runnable notebook: a single .ipynb you can download and open in Jupyter or VS Code to work through every exercise.
Extensions: suggested follow-up experiments so you don't stop at a faithful reimplementation.