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  Seminar Advanced Deep Learning (SemADL)

Lecturers
Prof. Dr.-Ing. habil. Andreas Maier, Dr.-Ing. Vincent Christlein, Prof. Dr.-Ing. Katharina Breininger, Prof. Dr. Joachim Hornegger

Details
Seminar
Online
2 cred.h, ECTS studies, ECTS credits: 5
nur Fachstudium, Sprache Englisch
Zeit: Mon 8:15 - 9:45

Fields of study
WPF INF-MA ab 1
WPF MT-MA-BDV ab 1
WPF CE-MA-TA-MT ab 1

Prerequisites / Organisational information
Registration via StudOn: https://www.studon.fau.de/crs4006742.html

Contents
Deep Learning-based algorithms showed great performance in many fields of image processing and pattern recognition and compete with technologies such as compressive sensing and iterative optimization. The basis for the success of these algorithms is the availability of large amounts of data (big data) for training and of high computing power (typically GPUs).
In this seminar we try to explore advanced deep learning methods. In particular, we will aim to develop a deeper understanding of certain topics, for example: graph neural networks, unsupervised learning, differentiable learning, invertible learning, neural ordinary differential equations, transfer learning, multi-task learning, uncertainty DL, etc.

ECTS information:
Credits: 5

Additional information
Keywords: algorithms; medical image processing
Expected participants: 10, Maximale Teilnehmerzahl: 10
Registration is required for this lecture.
Die Registration via: StudOn

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2021/2022:
Seminar Advanced Algorithms in Medical Image Processing (SemAAMIP)

Department: Chair of Computer Science 5 (Pattern Recognition)
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