Seminar Visualization techniques for neural networks, Summer Term 2018

Neural networks and deep-learning evolve to a technology embedded into many different aspects of our every-day routine.

Often, these techniques are viewed as black boxes without insights to their inner workings. Visualization techniques provide both developers and Users important insights into the functionality of neural networks. This can lead to further optimization of deep learning approaches, easier explanations for the functionality of those networks, usability even for non-experts and broader acceptance of such technologies.

In this seminar, we are going to investigate and analyze visualization techniques in the field of deep learning. Our question will be: How can training and analyzing neural networks be made more transparent?

Requirements

To successfully complete the seminar the following requirements have to be fulfilled:

  • Written paper on a selected topic, German or English (English preferred)
  • 20 minutes presentation with questions and answers at the end, German or English
  • Active participation in peer reviews and discussions
  • Meet the schedule

Allocation

Computer Science

  • B.Sc., Seminar Visual Computing (FPSO 2014)
  • B.Sc., Seminar Visual Computing - Bachelor (FPSO 2017)
  • M.Sc., Seminar Research Trends in Visual Computing (FPSO 2014)
  • B.Sc., Seminar Visual Computing - Master (FPSO 2017)

Media Informatics

  • B.Sc., Seminar Visual Computing (FPSO 2014)
  • B.Sc., Seminar Visual Computing - Bachelor (FPSO 2017)
  • M.Sc., Seminar Research Trends in Visual Computing (FPSO 2014)
  • B.Sc., Seminar Visual Computing - Master (FPSO 2017)

Software Engineering

  • B.Sc., Seminar Visual Computing (FPSO 2014)
  • B.Sc., Seminar Visual Computing - Bachelor (FPSO 2017)
  • M.Sc., Seminar Research Trends in Visual Computing (FPSO 2014)
  • B.Sc., Seminar Visual Computing - Master (FPSO 2017)

See Module Description at HIS/Study