30 citations · 45 across the 5 of their papers we have counts for
7 papers
Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation
Christoph Angermann, Markus Haltmeier, Ruth Steiger +2
Convolutional neural networks are state-of-the-art for various segmentation tasks. While for 2D images these networks are also computationally efficient, 3D convolutions have huge…
Analysis of regularized Nyström subsampling for regression functions of low smoothness
Shuai Lu, Peter Mathé, Sergiy Pereverzyev
This paper studies a Nyström type subsampling approach to large kernel learning methods in the misspecified case, where the target function is not assumed to belong to the reproduc…
Galaxy And Mass Assembly: Automatic Morphological Classification of Galaxies Using Statistical Learning
Sreevarsha Sreejith, Sergiy Pereverzyev, Lee S. Kelvin +15
We apply four statistical learning methods to a sample of galaxies () from the Galaxy and Mass Assembly (GAMA) survey to test the feasibility of using automated algo…
The quasi-optimality criterion in the linear functional strategy
Stefan Kindermann, Sergiy Pereverzyev, Andrey Pilipenko
The linear functional strategy for the regularization of inverse problems is considered. For selecting the regularization parameter therein, we propose the heuristic quasi-optimali…
Operator learning approach for the limited view problem in photoacoustic tomography
Florian Dreier, Sergiy Pereverzyev, Markus Haltmeier
In photoacoustic tomography, one is interested to recover the initial pressure distribution inside a tissue from the corresponding measurements of the induced acoustic wave on the…
A Galerkin least squares approach for photoacoustic tomography
Johannes Schwab, Sergiy Pereverzyev, Markus Haltmeier
The development of fast and accurate image reconstruction algorithms is a central aspect of computed tomography. In this paper we address this issue for photoacoustic computed tomo…
A Parameter Choice Strategy for the Inversion of Multiple Observations
C. Gerhards, S. Pereverzyev, P. Tkachenko
In many geoscientific applications, multiple noisy observations of different origin need to be combined to improve the reconstruction of a common underlying quantity. This naturall…