Mathis Hoffmann

According to our database, Mathis Hoffmann authored at least 12 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

DiffRenderGAN: Addressing Training Data Scarcity in Deep Segmentation Networks for Quantitative Nanomaterial Analysis through Differentiable Rendering and Generative Modelling.

Dennis Possart, Leonid Mill, Florian Vollnhals, Tor Hildebrand, Peter Suter, Mathis Hoffmann, Jonas Utz, Daniel Augsburger, Mareike Thies, Mingxuan Wu, Fabian Wagner, George Sarau, Silke H. Christiansen, Katharina Breininger

CoRR, February, 2025

2023

An Industry-Specific Investigation on Artificial Intelligence Adoption: The Cases of Financial Services and Manufacturing.

Mathis Hoffmann, Maren F. Mehler

Proceedings of the 27th Pacific Asia Conference on Information Systems, 2023

2021

Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning.

Lukas Bommes, Mathis Hoffmann, Claudia Buerhop-Lutz, Tobias Pickel, Jens Hauch, Christoph Brabec, Andreas K. Maier, Ian Marius Peters

CoRR, 2021

Module-Power Prediction from PL Measurements using Deep Learning.

Mathis Hoffmann, Johannes Hepp, Bernd Doll, Claudia Buerhop-Lutz, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein

CoRR, 2021

2020

Joint Super-Resolution and Rectification for Solar Cell Inspection.

Mathis Hoffmann, Thomas Köhler, Bernd Doll, Frank Schebesch, Florian Talkenberg, Ian Marius Peters, Christoph J. Brabec, Andreas Maier, Vincent Christlein

CoRR, 2020

Deep Learning-based Pipeline for Module Power Prediction from EL Measurements.

Mathis Hoffmann, Claudia Buerhop-Lutz, Luca Reeb, Tobias Pickel, Thilo Winkler, Bernd Doll, Tobias Würfl, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein

CoRR, 2020

2019

Learning with known operators reduces maximum error bounds.

Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke H. Christiansen

Nat. Mach. Intell., 2019

Learning with Known Operators reduces Maximum Training Error Bounds.

Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke H. Christiansen

CoRR, 2019

Weakly Supervised Segmentation of Cracks on Solar Cells Using Normalized Lp Norm.

Martin Mayr, Mathis Hoffmann, Andreas K. Maier, Vincent Christlein

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Fast and Robust Detection of Solar Modules in Electroluminescence Images.

Mathis Hoffmann, Bernd Doll, Florian Talkenberg, Christoph J. Brabec, Andreas K. Maier, Vincent Christlein

Proceedings of the Computer Analysis of Images and Patterns, 2019

2018

Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems.

Tobias Würfl, Mathis Hoffmann, Vincent Christlein, Katharina Breininger, Yixing Huang, Mathias Unberath, Andreas K. Maier

IEEE Trans. Medical Imaging, 2018

2017

A Robust Chessboard Detector for Geometric Camera Calibration.

Mathis Hoffmann, Andreas Ernst, Tobias Bergen, Sebastian Hettenkofer, Jens-Uwe Garbas

Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP, Porto, Portugal, February 27, 2017