Important information about the new lecture cycle

Starting with WS 2017/18, the previous lecture cycle repeating every year will be switched to a two-year cycle to accomodate upcoming changes in the Bachelor program.

The following lectures will be offered:

Although the lectures are numbered with I-IV in the official list, this does not mean you have to attend them in this exact order. They all stand on their own, and you can start at any point within the cycle. While you can of course expect some connections to be drawn between lectures, knowledge of any previous one will not mandatory, and all necessary background material will be introduced. All lectures are 4 SWS, with 3 lectures and 1 exercise group every two weeks, and will be accompanied by an optional seminar towards the end of the semester to cover advanced material.

This semester (WS 2017/18) is something of an exception, since I am just making the switch to the new cycle. I'll start with Part IV: Probabilistic Methods and Deep Learning. However, as I covered Probabilistic Methods just last semester as part of the old cycle, this lecture will solely focus on Deep Learning. Anyone can attend without pre-requisites.


Upcoming Seminar

The topic of this Winter Semester's Seminar in 2017 is "Deep Learning in Computer Vision".  Date of first meeting will be announced around the beginning of the semester. The format will be a block seminar with paper presentations, as well as a practical challenge to code and train your own network. Participation in the lecture is highly recommended to get the necessary background.

Student projects

Potential student research assistants interested in computer vision and image analysis are always welcome, please send an e-Mail to make an appointment.

If you are a Master's or Bachelor's student interested in a thesis project, you should have some background in image analysis or computer vision already. If you think you qualify, please make an appointment so we can discuss potential projects and topics.