30 citations · 30 across the 2 of their papers we have counts for
3 papers
cs.LG2019
Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck
Ilja Manakov, Markus Rohm, Volker Tresp
In this paper, we present an in-depth investigation of the convolutional autoencoder (CAE) bottleneck. Autoencoders (AE), and especially their convolutional variants, play a vital…
cs.CV2019
Push it to the Limit: Discover Edge-Cases in Image Data with Autoencoders
Ilja Manakov, Volker Tresp
In this paper, we focus on the problem of identifying semantic factors of variation in large image datasets. By training a convolutional Autoencoder on the image data, we create en…
eess.IV2019★ 30 cited
Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation
Ilja Manakov, Markus Rohm, Christoph Kern +3
We cast the problem of image denoising as a domain translation problem between high and low noise domains. By modifying the cycleGAN model, we are able to learn a mapping between t…