Lectures
The following LECTURE NOTES are available for the Czech students. They are intended for two courses, namely "Digital Image Processing" and "Image Analysis." Chapters 8 and following are intended for the course "Image Analysis." For English students, a brief extract is available HERE (still in development). However, please take both these materials with a grain of salt. Although what is written there is still valid, AI-based approaches are now widely used. On the other hand, if you know something about what is written there, you will better understand what is happening in modern approaches. For an introduction to deep neural networks, I will use the presentation that you can find HERE. We will also touch on GAN networks (HERE) and diffusion networks (HERE). I will continue to improve the presentation (especially before the corresponding lecture). Image analysis is an important part of AI, and fascinating things are constantly happening in this field.Exercises
Classroom-based exercises are led by my colleague Jan Gaura. The details can be sound here on his pages..
Exam
The exam is oral, with the option of written preparation (3 questions, each worth a maximum of 20 points; a score of 31 points is required to pass the exam). The exam may be taken only after receiving a passing grade in the lab. (A maximum of 40 points can be awarded for the lab exercises.) You can find the exam questions HERE (Czech students). The questions and instructions for the ERASMUS students are available HERE.