Department of Image Processing

Slajdy k prednaskam

Slajdy tvori zakladni studijni material, ale samy o sobe nestaci. Vzdy k nim ctete prislusnou cast z [A] a pokud mozno alespon orientacne z [1] (Lectures 2,3,4) nebo [3] (Lecture 5).

Lecture 1 Download

Lectures 2 and 3 Download

Lecture 4 Download

Lecture 5 Download

Lecture 6 Download

Povinna literatura

[A] Introduction to Object Recognition. Obsahuje spoustu uzitecnych referenci pro hlubsi studium.
Download

Doporučená literatura

[1] Duda R.O. et al., Pattern Classification, (2nd ed.), John Wiley, New York, 2001
Vyborna ucebnice, pokryvajici do hloubky vetsinu prednasek. Na nekolika serverech ke stazeni zdarma.

[2] Gonzales R. C. et al., Digital Image Processing using MATLAB, Prentice Hall, 2004.
Dobra pomucka ke cvicenim.

[3] Feature selection. Doplnkovy text k Lecture 5. Download

Materials for exercises

They will be added during the semester, for the current lesson.

Labs start here!

1. Zoom link: https://cesnet.zoom.us/j/95775148221
2. Get a link from your teacher, e.g. https://classroom.github.com/a/YspbK****
3. Sign in to GitHub
   What is GitHub?
   New to GitHub? Create an account.
   Start using GitHub.
4. If necessary, click on the "Authorize GitHub Classroom" button
5. Find your name in the list (only for the first assignment)
6. Click on "Accept the assignment"
7. Go to colab.research.google.com
8. Click on "Authorize Google Colab"
9. Click on "GitHub" (or File > Open Notebook > GitHub)
10. Type your GitHub user name (check "Include private repos")
11. Find the desired repository and the notebook file
12. Loading (In case of "Error", press "Retry")
13. If necessary, click on the "Authorize with GitHub" button
14. Edit the notebook
15. For the Final Project >> Save in GitHub (File > Save a copy in GitHub)

Lab 1 - SU1 - 25. 10. 2023 - 9:00 a.m.

Linear regression, K-NN
GitHub Classroom link

Lab 2 - SU1 - 8. 11. 2023 - 9:00 a.m.

SVM, Naive Bayes, K-Means Clustering
GitHub Classroom link

Lab 3 - SU1 - 15. 11. 2023 - 9:00 a.m.

Perceptron, Decision Tree, Random Forest
GitHub Classroom link

Lab 4 - SU1 - 29. 11. 2023 - 9:00 a.m.

PCA, SVD, LDA
GitHub Classroom link

Lab 5 - SU1 - 6. 12. 2023 - 9:00 a.m.

RANSAC, AdaBoost
GitHub Classroom link

FINAL PROJECTs - SU1 - 13. 12. 2023 - 9:00 a.m.

Each student has to choose a final project to defend in front of the others (online) in the last class.
The topic must be selected by the end of November and written in the class book below.
GitHub Classroom link