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Technical University of Munich

Technical University of Munich

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Practical Course: Learning For Self-Driving Cars and Intelligent Systems (10 ECTS)

WS 19, TU München

Correspondence

Please forward any queries related to the lab to: intellisys-ws19@vision.in.tum.de

Course Registration

Assignment to the lab is done via the matching system. Please additionally send your application documents to the correspondence email. See the preliminary meeting slides for more details.

The preliminary meeting (recommended) to take took place on Wednesday, 10 July 2019 at 4pm in HS 2 (00.04.011).

Course Content

Learning-based approaches have recently made tremendous progress in the computer vision and robotics research community. In this practical course, we will solve challenging real-world problems in the area of self-driving cars and intelligent systems. Topics will be in the direction of perception, control, and environmental understanding. This may also involve working on massive datasets including unstructured or unordered data.

Pre-requisites
  • Good knowledge of the Python language and basic mathematics such as linear algebra, analysis, and numerics is required.
  • Good knowledge of a deep learning framework such as PyTorch, TensorFlow, etc.
  • Participation in at least one of the offered deep learning lectures at TUM is required.
Structure

Students will work in groups of 2 persons on research oriented projects from the beginning of the semester. Assignment of projects to groups will be done in the first week. There will be biweekly presentations to share results/findings among the groups. To review progress and assist with resolving any issues, students are invited to meet the supervisors on a weekly basis.

Schedule

Time: Tuesdays 2-4pm
Room: 03.11.018

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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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