NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (15)

math.AP2017

Analysis of the Linearized Problem of Quantitative Photoacoustic Tomography

Markus Haltmeier, Lukas Neumann, Linh V. Nguyen +1

astro-ph.GA2017

Galaxy And Mass Assembly: Automatic Morphological Classification of Galaxies Using Statistical Learning

Sreevarsha Sreejith, Sergiy Pereverzyev, Lee S. Kelvin +15

math.AP2017

Analysis of Iterative Methods in Photoacoustic Tomography with Variable Sound Speed

Markus Haltmeier, Linh V. Nguyen

cs.CV2018

Deep Learning for Photoacoustic Tomography from Sparse Data

Stephan Antholzer, Markus Haltmeier, Johannes Schwab

math.FA2008

Sparse Regularization with $l^q$ Penalty Term

Markus Grasmair, Markus Haltmeier, Otmar Scherzer

math.NA2019

Analysis of the Block Coordinate Descent Method for Linear Ill-Posed Problems

Simon Rabanser, Lukas Neumann, Markus Haltmeier

math.AP2019

Explicit inversion formulas for the two-dimensional wave equation from Neumann traces

Florian Dreier, Markus Haltmeier

math.AP2013

Inversion of circular means and the wave equation on convex planar domains

Markus Haltmeier

math.NA2019

Sparse synthesis regularization with deep neural networks

Daniel Obmann, Johannes Schwab, Markus Haltmeier

The paper introduces a sparse reconstruction framework for inverse problems that trains an encoder‑decoder network with an ℓ¹ penalty, enabling sparse signal recovery via threshold…

#sparse reconstruction#encoder-decoder networks#ℓ¹ regularization#inverse problems
cs.CV2019

Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation

Christoph Angermann, Markus Haltmeier, Ruth Steiger +2

The paper proposes a projection-based 2.5D U‑net that replaces 3D convolutions with max‑intensity projections and 2D convolutions, enabling faster training and lower memory use whi…

#volumetric segmentation#2.5d networks#projection-based methods#u-net architecture
eess.IV2019

Learned backprojection for sparse and limited view photoacoustic tomography

Johannes Schwab, Stephan Antholzer, Markus Haltmeier

math.AP2014

Universal inversion formulas for recovering a function from spherical means

Markus Haltmeier

cs.CV2018

Image Based Fashion Product Recommendation with Deep Learning

Hessel Tuinhof, Clemens Pirker, Markus Haltmeier

math.AP2015

Single-stage reconstruction algorithm for quantitative photoacoustic tomography

Markus Haltmeier, Lukas Neumann, Simon Rabanser

math.OC2017

Efficient regularization with wavelet sparsity constraints in PAT

Jürgen Frikel, Markus Haltmeier