2 citations · 2 across the 3 of their papers we have counts for
4 papers · 1 filter
Denoising OCT Images Using Steered Mixture of Experts with Multi-Model Inference
Aytaç Özkan, Elena Stoykova, Thomas Sikora +1
In Optical Coherence Tomography (OCT), speckle noise significantly hampers image quality, affecting diagnostic accuracy. Current methods, including traditional filtering and deep l…
Steered Mixture-of-Experts Autoencoder Design for Real-Time Image Modelling and Denoising
Elvira Fleig, Erik Bochinski, Thomas Sikora
Research in the past years introduced Steered Mixture-of-Experts (SMoE) as a framework to form sparse, edge-aware models for 2D- and higher dimensional pixel data, applicable to co…
Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression
Elvira Fleig, Jonas Geistert, Erik Bochinski +2
Steered-Mixtures-of-Experts (SMoE) models provide sparse, edge-aware representations, applicable to many use-cases in image processing. This includes denoising, super-resolution an…
Accelerated Deep Lossless Image Coding with Unified Paralleleized GPU Coding Architecture
Benjamin Lukas Cajus Barzen, Fedor Glazov, Jonas Geistert +1
We propose Deep Lossless Image Coding (DLIC), a full resolution learned lossless image compression algorithm. Our algorithm is based on a neural network combined with an entropy en…