1 code implementation • 13 Sep 2023 • Thomas Germer, Jan Robine, Sebastian Konietzny, Stefan Harmeling, Tobias Uelwer
A CT scanner consists of an X-ray source that is spun around an object of interest.
2 code implementations • 22 Aug 2023 • Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner, Marc Höftmann, Eric Upschulte, Sebastian Konietzny, Maike Behrendt, Stefan Harmeling
Learning meaningful representations is at the heart of many tasks in the field of modern machine learning.
1 code implementation • 13 Mar 2023 • Jan Robine, Marc Höftmann, Tobias Uelwer, Stefan Harmeling
Deep neural networks have been successful in many reinforcement learning settings.
Model-based Reinforcement Learning reinforcement-learning +1
1 code implementation • 31 May 2022 • Tobias Uelwer, Sebastian Konietzny, Stefan Harmeling
With extensive experiments on the Fourier phase retrieval problem and thorough ablation studies, we can show the benefits of our modified ILO and the new initialization schemes.
1 code implementation • 30 May 2022 • Thomas Germer, Tobias Uelwer, Stefan Harmeling
Our method consists of three steps: First, we estimate a warping transformation of the images to align the sharp images with the blurred ones.
1 code implementation • NeurIPS Workshop Deep_Invers 2021 • Tobias Uelwer, Nick Rucks, Stefan Harmeling
In this work, we consider a modified version of the phase retrieval problem, which allows for a reference image to be added onto the image before the Fourier magnitudes are measured.
no code implementations • 9 Jul 2021 • Tobias Uelwer, Felix Michels, Oliver De Candido
Our method is able to detect adversarial examples generated by various attacks, and can be easily adopted to a plethora of deep classification models.
no code implementations • 18 Jun 2021 • Stefan Wagner, Michael Janschek, Tobias Uelwer, Stefan Harmeling
We propose a new approach to increase inference performance in environments that require a specific sequence of actions in order to be solved.
no code implementations • 18 Jun 2021 • Tobias Uelwer, Tobias Hoffmann, Stefan Harmeling
Fourier phase retrieval is the problem of reconstructing a signal given only the magnitude of its Fourier transformation.
no code implementations • 12 Oct 2020 • Jan Robine, Tobias Uelwer, Stefan Harmeling
Sample efficiency remains a fundamental issue of reinforcement learning.
Ranked #27 on Atari Games on Atari 2600 Pong
1 code implementation • 26 Jun 2020 • Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling
Alpha matting aims to estimate the translucency of an object in a given image.
1 code implementation • 25 Mar 2020 • Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling
Alpha matting describes the problem of separating the objects in the foreground from the background of an image given only a rough sketch.
1 code implementation • 10 Dec 2019 • Tobias Uelwer, Alexander Oberstraß, Stefan Harmeling
In this paper, we propose the application of conditional generative adversarial networks to solve various phase retrieval problems.
1 code implementation • 9 Jun 2019 • Felix Michels, Tobias Uelwer, Eric Upschulte, Stefan Harmeling
This paper extensively evaluates the vulnerability of capsule networks to different adversarial attacks.