Organizer: M.Sc. Sina Shafaei
Contact: shafaei (at) in.tum.de
Registration: Via Matching System and Submitted Application
Semester: Winter Semester 2019/20
Target Group: Highly motivated master students interested in research
Time & Location: 15:00-17:00 / 02.09.023 (Kick off session + presentation dates)
- Slides of the kick-off session (18.10.2019): Here
- The first official session of the seminar, for the registered students, will be on 18.10.2019, 15:00-17:00 at seminar room: 02.09.023.
- There is no preliminary (pre-course) session for this seminar, registration is only possible by submitting an application of interest over email and respectively applying through matching system.
The main focus of this seminar is to study the challenges, methods and approaches which exists on the way of deploying the AI applications in a real autonomous vehicle. Developed technologies for enabling the autonomy of a vehicle will be investigated from the perspective of safety frameworks and hardware platforms as well. Moreover, the students will investigate the state-of-the-art developments in both dimensions of the software (like scaling the neural networks) and hardware (like neuromorphic boards) domains.
In our first session on 18.10.2019 students will form their group (of two members) and we will discuss the available topics. Each group will get assigned to one topic according to their own preference. Groups will collect the necessary materials (state of the art scientific works e.g. scientific publications) within the context of their topic and will perform their research based on the collected resources. Each group will be given 40 minutes on their specified date (are listed in below) to represent the findings, and address the research questions of their own topic. Respectively, they will write and submit a scientific paper (IEEE template) with minimum 6 pages, depicting their findings and the main contribution of their work during seminar.
|A- Enabling Collision Avoidance Systems in Autonomous Vehicles||10.01.2020|
|B- Maintaining Emotional Awareness in Highly/Fully Autonomous Driving||10.01.2020|
|C- Recent Advancements and Approaches for Scaling ML-based Models on Embedded Systems||17.01.2020|
|D- Deep Learning on Embedded Systems / Use Case: eFPGA||17.01.2020|
|E- Integration of Autonomous Driving Applications on Neuromorphic Boards||24.01.2020|
|F- Scheduling Approaches for ML-based Applications in Autonomous Vehicle||24.01.2020|