Neural networks in image processing
The course covers typical applications of neural networks in image processing. Introductory lectures teach algorithms for various image processing disciplines and explain their implementation in the world of neural networks. Special attention is given to the fundamentals of neural networks and their implementation in MATLAB. The focus of the course is a supervised computer lab, in which students work on classic image processing tasks with neural networks and apply metrological analysis tools. Possible implementations of learned image processing methods are discussed using exemplary applications in medicine and communications engineering. Students are encouraged to contribute their own creative solutions to the course.
Computer Science program
Neural Networks in Image Processing is part of the minor subject “Computational Laser Metrology,” module INF-D-510 Fundamentals of the Minor Subject (L/T/P: 0/2/0)
Electrical Engineering program
The three digital experiments can be completed instead of the practical experiments as part of the MT internship (L/T/P: 0/0/1) MT internship
You can also deepen your knowledge as part of a diploma thesis, student research project, advanced seminar, or as a student research assistant at our chair. You can find further offers in this overview.
The course is open to students of computer science and electrical engineering. Prior knowledge of mathematics (integral calculus, Fourier transform, statistics) is expected.
Please register for the course in OPAL-Course to participate.
Currently, it is planned that the course and the supervision of the computer lab will take place in person.
If you have any questions about the course, please contact the organizer Tom Glosemeyer.
Winter semester 2025/26
When & where: Friday, 3rd DS (11:10 a.m. - 12:40 p.m.) GÖR/0226
Introductory session: October 17, 2025
Content:
1. Introduction to digital image processing and neural networks 2. Experiment 1: Classification of digits 3. Experiment 2: Reconstruction of digits through a scattering medium 4. Experiment 3: Mode decomposition through a multimode fiber