- Course Website: https://web.eecs.umich.edu/~justincj/teaching/eecs498/
- Instructor: Justin Johnson
| # | Content | Slide |
|---|---|---|
| Lecture 1 | Introduction to Deep Learning for Computer Vision | Slide 01 |
| Lecture 2 | Image Classification | Slide 02 |
| Lecture 3 | Linear Classifiers | Slide 03 |
| Lecture 4 | Optimization | Slide 04 |
| Lecture 5 | Neural Networks | Slide 05 |
| Lecture 6 | Backpropagation | Slide 06 |
| Lecture 7 | Convolutional Networks | Slide 07 |
| Lecture 8 | CNN Architectures | Slide 08 |
| Lecture 9 | Hardware and Software | Slide 09 |
| Lecture 10 | Training Neural Networks I | Slide 10 |
| Lecture 11 | Training Neural Networks II | Slide 11 |
| Lecture 12 | Recurrent Networks | Slide 12 |
| Lecture 13 | Attention | Slide 13 |
| Lecture 14 | Visualizing and Understanding CNNs | Slide 14 |
| Lecture 15 | Object Detection | Slide 15 |
| Lecture 16 | Detection and Segmentation | Slide 16 |
| Lecture 17 | 3D Vision | Slide 17 |
| Lecture 18 | Videos | Slide 18 |
| Lecture 19 | Generative Models I | Slide 19 |
| Lecture 20 | Generative Models II | Slide 20 |
| Lecture 21 | Reinforcement Learning | Slide 21 |
| Lecture 22 | Conclusion | Slide 22 |