Neural Networks in Image Processing
The course deals with typical applications of neural networks in image processing. Algorithms for various image processing disciplines are taught in introductory lectures and their implementation in the world of neural networks is explained. Special attention is paid to the basics of neural networks and their implementation in MATLAB. The focus of the course is a mentored computer lab in which the students work on classical tasks of image processing with neural networks and apply metrological analysis tools. Possible realisations of methods taught are discussed using exemplary applications in medical and communications engineering. The students are encouraged to bring their own and creative approaches to solutions into the course.
Electrical Engineering, Mechatronics (Studiengänge Elektrotechnik, Mechatronik)
The Neural Network course can be done instead of the practical experiments of the measurement technique lab course (Messtechnik II Praktikum). ET-120806, MT-120825 (V/Ü/P: 0/0/1)
Please Note: the course is also part of the minor subject „Computational Laser Metrology“, module INF-D-510 (V/Ü/P: 0/2/0) for Computer Science, but takes place only during the Winter term.
You can also intensify your knowledge in the context of a diploma thesis (Diplomarbeit), student research project (Studienarbeit), advanced seminar (Oberseminar) or as a SHK at our chair. You can find offers in this overview (LINK).
The course can be attended by students of computer science and electrical engineering. Prior knowledge of mathematics (integral calculus, Fourier transformation, statistics) is expected.
For participation, please sign up to the course in OPAL.
We are currently planning to run the course in-person.
If you have any questions regarding the course, please contact the organiser Qian Zhang ()
Summer term 2022
Day & time: The course is expected to start in the third week of the semester (18th to 22nd April). Students of electrical engineering must first enrol in the measurement technique lab course (LINK: Messtechnik II Praktikum). Afterwards, you will be informed of the possibility to enrol in the Neural Networks course.
Content:
1. Introduction to image processing in MATLAB
2. Introduction to Neural Networks with implementation in MATLAB
3. Presentation of the 3 computer lab excercises
Excercise 1
Excercise 2
Excercise 3
Verantwortlicher Hochschullehrer | Organisation | |
Prof. Dr.-Ing. habil. Jürgen Czarske | Dipl.-Ing. Stefan Rothe |