In the lecture, technological basics, historical backgrounds and the resulting workflows in production are taught. In the seminars presented algorithms and procedures are implemented with the help of Python OpenGL, and GLUT. The aim is to deepen the contents of the lectures and to practically create one's own 3D software. In addition, the handling of programming languages and object-oriented programming will be learned.
Main topics of the lecture are: History of television technology, psycho-optics, analogue television systems, transmission technology, modulation methods, digital television systems.
In this project workshop, machine learning approaches using Python and PyTorch will be applied to audio signals. The goal is the recognition and separation of sounds or audio sources, such as the separation of audio sources, the recognition of noise or spoken keywords, and the decomposition of audio signals with a filter bank learned from the signal into its "sound atoms".