Deep Learning for imaging
Deep Learning for imaging
1. Basics of image handling and processing
2. Very accessible deep learning
3. Tensor calculations
4. Simple neural net with PyTorch
5. Training a network
6. Handling data
7. Data augmentation
8. Simplifying code with PyTorch-Lightning
9. Classification: practice
10. Convolutions and rescaling
11. Autoencoder
12. Transfer learning
13. Segmentation
14. U-net
15. Unet applied to nuclei segmentation
Index