Project Representation Learning (PRL)- Lecturers
- Prof. Dr. Bernhard Kainz, Johanna Müller, M. Sc., Mischa Dombrowski, M. Sc.
- Details
- Sonstige Lehrveranstaltung
Online
8 cred.h, ECTS studies, ECTS credits: 10
nur Fachstudium, Sprache Deutsch und Englisch
Zeit:
- Fields of study
- WPF AI-MA ab 1
WPF MT-BA-BV ab 1
WPF INF-BA ab 1
WPF DS-MA-DW ab 1
- Prerequisites / Organisational information
- recommended:
Deep Learning ML Prof. Dr. Andreas Maier 2+2 5 x E
Pattern Recognition ML Prof. Dr. Andreas Maier 3+1+2 5 x E
Maschinelles Lernen für Zeitreihen ML Prof. Eskofier, Prof. Oliver Amft, Dr. Ch. Mutschler 2+2+2 7.5 x E
- Contents
- Different projects in the area of (deep) representation learning are on offer. These reach from theoretical exploration of new data representation methods to practical evaluation of applications in, e.g., medical image analysis.
Example projects will be made available on the website of the IDEA Lab https://idea.tf.fau.eu/. Students may also propose their own projects, which will be coordinated and refined with the module lead during preliminary discussions.
- Recommended literature
- A specific reading list will be established at the beginning of each project, general literature is listed below:
Quinn J, McEachen J, Fullan M, Gardner M, Drummy M. Dive into deep learning: Tools for engagement. Corwin Press; 2019 Jul 15. https://d2l.ai/
Goodfellow I, Bengio Y, Courville A, Bengio Y. Deep learning. Cambridge: MIT press; 2016 Nov 18. https://www.deeplearningbook.org/
- ECTS information:
- Credits: 10
- Additional information
- Expected participants: 10, Maximale Teilnehmerzahl: 20
- Verwendung in folgenden UnivIS-Modulen
- Startsemester SS 2022:
- Project Representation Learning (PRL)
- Department: W3-Professur für Image Data Exploration and Analysis
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