Teaching

Computer Vision Laboratory  (Spring 2024)

1. Image  Fundamental

2. Image stitching with SIFT

3. Camera Calibration 

4. Canny&Hough Transform

5. Pytorch Basics

6. Automatic Differentiation 

7. Neural Networks

8. Networks Architectures

9. Network Training&Fine Tuning

10. Batch Normalization (Esempio)

11. Region Proposal

12. Train a Yolov8 object detection on a Custom Dataset (RoboFlow)

13. A Walkthrough of Vision Transformer

14. Variational Auto Encoder (VAE)

15. Generative Adversarial Network (GAN)

16. Project Tips

Computer Vision Laboratory  (Spring 2022)

(Colab Notebook)

What is Colab? 

What is Python? 

Image Manipulating

Affine Tranforms 

Image Tranforms

Image Filtering

Spatial Filtering 

2D Fourier Transform

Tensors basics

Tensors operations

Linear models & Pytorch Datasets

Logistic Regression & Optimization

Convolutional Neural Network

Uncertainty, regularization, deep learning tools