teaching

Deep Learning for Computer Vision

The lecture covers deep learning and its applications to computer vision. The following topics are covered:

• Fundamentals of deep learning (artificial neural networks, training via stochastic gradient descent)
• Convolutional neural networks and their application to image recongnition
• Deep learning approaches for vision tasks: segmentation, object detection, denoising, etc.
• Generative models (Variational Autoencoders, Generative Adverserial Networks) and their applications in image synthesis
• Semi-supervised, weakly-supervised and self-supervised learning for image data
• Vision transfomers
• Deep learning for videos, point clouds and scene rendering

The lecture is held every winter term and consists of one lecture per week and exercises. The module description can be found here.

Deep Learning in Biology and Medicine

The seminar discusses advanced topics in applications of deep learning methods in biology and medicine. We cover applications in image analysis, structural biology (e.g. protein folding with Alpha Fold), large language models in medicine and more. The seminar is offered every summer term.

Thesis and student projects

We are currently not offering any thesis topics. Previous topics have been on the application of deep learning and computer vision in biology and medicine. You can find an overview of previous projects here. New projects will be offered in the winter term 2025.