Instructors: Prof. Dr. Nassir Navab, Dr. Shahrooz Faghih Roohi,  Ashkan Khakzar, Azade Farshad, Anees Kazi

Registration

• Registration must be done through TUM Matching Platform (please pay attention to the Deadlines)
• In order to increase your priority, please also apply via our own Registration system.
• The maximum number of participants: 24.

Announcements

• The preliminary meeting slides can be found here: MLMIWs21-22.pdf
• The preliminary meeting is scheduled for July 7, 16:00 (Zoom link is visible on TUMonline in the course description).
• Due to the current pandemic, the seminar happens virtually via Zoom (the meeting link will be shared with participants via email).

Introduction

• The aim of the course is to provide the students with notions about various machine learning techniques. The course is subdivided into a lecture/excercises block and a project.
  • The lectures will include DL topics relevant to medical imaging applications. Each lecture will be followed by a practical hands-on exercise (e.g. the implementation in Python).
  • The topics of the projects will be distributed at the beginning of the semester. Each topic will be supervised by a different person. The projects are to be realized by couples.

Course Structure

In this Master Praktikum (Hauptseminar), students select one scientific article from the list provided by course organizers. The students read the paper, and must accomplish the following:

• Presentation: 50% Intermediate and Final Presentation (Done by all tutors -- mainly on your presentation skill, progress so far compared to other groups ...etc.)
  • Use the CAMP templates for PowerPoint camp-tum-jhu-slides.zip
  • The guideline for mid-presentation can be found here: GuidelineMLMI_MidPresentation.pdf
  • The guideline for the final presentation can be found here: GuidelineMLMI_Final presentation_WS2021-22.pdf
• Project Progress: 50% Project Progress (Done by your tutor -- mainly on your weekly progress on lrz git repository.

Schedule

Projects