Stu­dent theses

Below are our current open bachelor and master thesis topics. If you are interested in learning more about a topic, please contact the person assigned to that topic or visit us at our offices.

You can also contact our team members for more currently open theses topics or if you want to suggest a topic yourself!

 

Open Bach­el­or Thes­is Top­ics

Kontakt: Adrian Redder
Details zur Bachelorarbeit finden Sie hier.

Kontakt: Adrian Redder

Details zur Bachelorarbeit finden Sie hier.

Open Mas­ter Thes­is Top­ics

Contact: Julio Betancourt 
Please find details about the master thesis here.

Contact: Julio Betancourt 
Please find details about the master thesis here.

Contact: Julio Betancourt 
Please find details about the master thesis here.

Contact: Julio Betancourt 
Please find details about the master thesis here.

Contact: Adrian Redder
Please find details about the master thesis here.

Master’s thesis, in a collaboration with Aarhus University, Denmark
Deep learning has led to the development of end-to-end methods for visual odometry (VO), setting up a new paradigm for this family of algorithms. The higher-level representation of the environment that deep learning introduces allows it to generate estimates under challenging imaging conditions that make traditional algorithms fail. However, their performance is conditioned by the selected training environment. This limitation has been mainly addressed by feeding more and more varied data to the network. The present work aims to assess the information in the datasets from which the algorithm is learning. For that, a set of metrics to deploy on the target datasets will be developed. The aim of these metrics is twofold: firstly, to assess the quality and variability of the data available, and secondly, to establish a criterion for the data splitting in learning-based VO.
Contact: Erdal Kayacan