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teaching:ws2019:intellisys_ws2019 [2019/07/05 15:13] Qadeer Khan |
teaching:ws2019:intellisys_ws2019 [2019/07/09 11:04] Qadeer Khan |
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**Organizers**: | **Organizers**: | ||
- | [[members: | + | [[members: |
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The preliminary meeting (recommended) to take place on **Wednesday, | The preliminary meeting (recommended) to take place on **Wednesday, | ||
- | Slides pertaining to the lab will be made available after the preliminary meeting | + | Slides pertaining to the lab will be made available after the preliminary meeting. |
+ | |||
+ | Please forward your questions to [[intellisys-ws19.vision.in@tum.de]] | ||
+ | == 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. |