139 citations · 555 across the 26 of their papers we have counts for
5 papers · 1 filter
Regularized Orthogonal Nonnegative Matrix Factorization and -means Clustering
Pascal Fernsel, Peter Maass
In this work, we focus on connections between -means clustering approaches and Orthogonal Nonnegative Matrix Factorization (ONMF) methods. We present a novel framework to extrac…
An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt +4
Deep image prior (DIP) was recently introduced as an effective unsupervised approach for image restoration tasks. DIP represents the image to be recovered as the output of a deep c…
Conditional Invertible Neural Networks for Medical Imaging
Alexander Denker, Maximilian Schmidt, Johannes Leuschner +1
Over the last years, deep learning methods have become an increasingly popular choice to solve tasks from the field of inverse problems. Many of these new data-driven methods have…
Generalization of the Change of Variables Formula with Applications to Residual Flows
Niklas Koenen, Marvin N. Wright, Peter Maaß +1
Normalizing flows leverage the Change of Variables Formula (CVF) to define flexible density models. Yet, the requirement of smooth transformations (diffeomorphisms) in the CVF pose…
Deeply supervised UNet for semantic segmentation to assist dermatopathological assessment of Basal Cell Carcinoma (BCC)
Jean Le'Clerc Arrastia, Nick Heilenkötter, Daniel Otero Baguer +6
Accurate and fast assessment of resection margins is an essential part of a dermatopathologist's clinical routine. In this work, we successfully develop a deep learning method to a…