# Talks

Talks 1 to 10 of 456 | show all

Date Time Venue Talk
09/23/20 10:00 am Zoom Verbesserung eines Segmentieralgorithmus für flache Fingerabdrücke auf Basis einer vergleichenden Analyse [Bachelorarbeit]
Thomas Plotz
09/11/20 03:00 pm Am Schwarzenberg-Campus 3 (E), Room 3.074 / Online-Stream Rationale Aktivierungsfunktionen in neuronalen Netzen (Bachelorarbeitsvortrag)
Fabian Bahr
09/10/20 03:30 pm (Zoom Link wird am 09.09. per E-Mail angekündigt) Bildsegmentierung durch Deep Learning mit U-Net und dem Mumford-Shah-Funktional [Bachelorarbeit]
Jannik Jacobsen
08/26/20 04:00 pm Am Schwarzenberg-Campus 3 (E), Room 3.074/75 Fast Strategies for Waiter-Client and Client-Waiter Games [Bachelorarbeit]
Sophie Externbrink, E-10
08/24/20 03:00 pm Am Schwarzenberg-Campus 3 (E), Room 3.074 / Online-Stream Neuronale Netze basierend auf Radiale-Basis-Funktionen (Bachelorarbeitsvortrag)
Marcel Franz
08/10/20 03:30 pm Zoom On the Axioms of Quantum Mechanics
Dennis Schmeckpeper

This will be an introductory talk on how the fundamental assumptions of quantum mechanics are modeled and how this relies on the spectral theory of unbounded self-adjoint operators on separable Hilbert spaces.
08/03/20 03:30 pm Zoom $\mathcal{H}_2 \otimes \mathcal{L}_\infty$-Optimal Model Order Reduction
Rebekka Beddig

I will introduce myself and present the topic of my master thesis.

In my thesis, I derived a method for model order reduction of parametric linear time-invariant systems. With this method we can compute parametric reduced-order models that are optimal with respect to the $\mathcal{H}_2 \otimes \mathcal{L}_\infty$-error. The method combines interpolatory methods with numerical optimization. We furthermore discuss the computation of the $\mathcal{H}_2 \otimes \mathcal{L}_\infty$-error and have a look at some numerical results.
07/27/20 03:00 pm Zoom Time-parallel flow estimation
Sebastian Götschel

Deformable image registration is a key technology in medical imaging; there the goal is to compute a meaningful spatial correspondence between two or more images of the same scene. One approach is to use an optimal control formulation to compute a stationary velocity field that parameterize the deformation map. The same methods can be used to estimate the motion of contrast agents from 3d ultrasound images.

This is work-in-progress; in the talk I’ll introduce the application problem and discuss computational techniques for its solution, with a focus on using parallelization in time to reduce the time-to-solution. It should be accessible for a broad audience.
07/23/20 11:00 am Am Schwarzenberg-Campus 3 (E), Room 3.074 PDE-Constrained Optimization of Parabolic Problems [Masterarbeit]
Judith Angel
07/21/20 04:00 pm Zoom Vortrag (Zoom Link wird am 21.07. per E-Mail angekündigt) Geometric Deep Learning in Medical Image Segmentation and Comparisons with UNET (Masterarbeit)
Björn Przybyla