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 is scheduled for July 21st, from 13:00 to 13:30 with the following zoom link:

https://tum-conf.zoom.us/j/68880327576

Meeting ID: 688 8032 7576

Passcode: 144823

• 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

• 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_WS2022-23.pdf
• Project Progress: 50% Project Progress (Done by your tutor -- mainly on your weekly progress on lrz git repository.)

Schedule

Projects