Mathis Hoffmann

Mathis Hoffmann, M. Sc.

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room 09.153
Martensstr. 3
91058 Erlangen

Phone number: +49 9131 85-25246
Fax number: +49 9131 85-27270
Email: mathis.hoffmann@fau.de
Website: https://lme.tf.fau.de/person/mhoffmann/

CV

Please refer to my LinkedIn profile.

Projects

2018

Analysis of Defects on Solar Power Cells

(Third Party Funds Group – Sub project)

Overall project: iPV 4.0: Intelligente vernetzte Produktion mittels Prozessrückkopplung entlang des Produktlebenszyklus von Solarmodulen
Term: August 1, 2018 - July 31, 2021
Funding source: Bundesministerium für Wirtschaft und Technologie (BMWi)

Abstract

Over the last decade, a large number of solar power plants have been installed in Germany. To ensure a high performance, it is necessary to detect defects early. Therefore, it is required to control the quality of the solar cells during the production process, as well as to monitor the installed modules. Since manual inspections are expensive, a large degree of automation is required.
This project aims to develop a new approach to automatically detect and classify defects on solar power cells and to estimate their impact on the performance. Further, big data methods will be applied to identify circumstances that increase the probability of a cell to become defect. As a result, it will be possible to reject cells in the production that have a high likelihood to become defect.

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Publications

2024

Journal Articles

Lüer L., Forberich K., Hepp J., Buerhop-Lutz C., Winkler T., Rodrigues S., Hoffmann M., Doll B., Hauch J., Brabec C., Peters IM.:
PV module power prediction by deep learning on electroluminescence images - Assessing the physics learned by a convolutional neural network
In: Solar Energy Materials and Solar Cells 264 (2024), Article No.: 112621
ISSN: 0927-0248
DOI: 10.1016/j.solmat.2023.112621
BibTeX: Download

2022

Journal Articles

Bommes L., Hoffmann M., Buerhop-Lutz C., Pickel T., Hauch J., Brabec C., Maier A., Peters IM.:
Anomaly detection in IR images of PV modules using supervised contrastive learning
In: Progress in Photovoltaics (2022)
ISSN: 1062-7995
DOI: 10.1002/pip.3518
BibTeX: Download

2021

Journal Articles

Hoffmann M., Köhler T., Doll B., Schebesch F., Talkenberg F., Peters IM., Brabec C., Maier A., Christlein V.:
Joint Super-Resolution and Rectification for Solar Cell Inspection
In: IEEE Journal of Photovoltaics 11 (2021), p. 1051-1058
ISSN: 2156-3381
DOI: 10.1109/JPHOTOV.2021.3072229
URL: https://arxiv.org/pdf/2011.05003.pdf
BibTeX: Download
Hoffmann M., Buerhop-Lutz C., Reeb L., Pickel T., Winkler T., Doll B., Würfl T., Peters IM., Brabec C., Maier A., Christlein V.:
Deep Learning-based Pipeline for Module Power Prediction from EL Measurements
In: Progress in Photovoltaics: Research and Applications (2021)
ISSN: 1099-159X
DOI: 10.1002/pip.3416
BibTeX: Download
Doll B., Hepp J., Hoffmann M., Schuler R., Buerhop-Lutz C., Peters IM., Hauch J., Maier A., Brabec C.:
Photoluminescence for Defect Detection on Full-Sized Photovoltaic Modules
In: IEEE Journal of Photovoltaics (2021)
ISSN: 2156-3381
DOI: 10.1109/JPHOTOV.2021.3099739
BibTeX: Download

Conference Contributions

Hoffmann M., Hepp J., Doll B., Buerhop-Lutz C., Peters IM., Brabec C., Maier A., Christlein V.:
Module-Power Prediction from PL Measurements using Deep Learning
(2021)
ISSN: 0160-837
DOI: 10.1109/PVSC43889.2021.9519005
URL: https://arxiv.org/pdf/2108.13640.pdf
BibTeX: Download
Doll B., Hepp J., Hoffmann M., Talkenberg F., Schüler R., Baier M., Buerhop-Lutz C., Tegtmeyer D., Peters IM., Hauch J., Brabec C.:
Outdoor photoluminescence of large area photovoltaic modules
SPIE Organic Photonics + Electronics, 2021 (San Diego, California, August 1, 2021 - August 5, 2021)
In: Proceedings Volume 11809, Organic, Hybrid, and Perovskite Photovoltaics XXII 2021
DOI: 10.1117/12.2593894
BibTeX: Download

2019

Journal Articles

Würfl T., Hoffmann M., Aichert A., Maass N., Dennerlein F., Maier A.:
Calibration-free beam hardening reduction in x-ray CBCT using the epipolar consistency condition and physical constraints.
In: Medical Physics 46 (2019), p. e810-e822
ISSN: 0094-2405
DOI: 10.1002/mp.13625
BibTeX: Download
Maier A., Syben-Leisner C., Stimpel B., Würfl T., Hoffmann M., Schebesch F., Fu W., Mill L., Kling L., Christiansen SH.:
Learning with Known Operators reduces Maximum Training Error Bounds.
In: Nature Machine Intelligence 1 (2019), p. 373-380
ISSN: 2522-5839
DOI: 10.1038/s42256-019-0077-5
BibTeX: Download

Conference Contributions

Buerhop-Lutz C., Hoffmann M., Reeb L., Pickel T., Hauch J., Maier A.:
Applying Deep Learning Algorithms to EL-images for Predicting the Module Power
36th European Photovoltaic Solar Energy Conference and Exhibition (Marseille, September 9, 2019 - September 13, 2019)
In: Proceedings of the 36th European Photovoltaic Solar Energy Conference and Exhibition 2019
DOI: 10.4229/EUPVSEC20192019-4CO.1.2
BibTeX: Download
Mayr M., Hoffmann M., Maier A., Christlein V.:
Weakly Supervised Segmentation of Cracks on Solar Cells using Normalized Lp Norm
2019 IEEE International Conference on Image Processing (Taipei, September 22, 2019 - September 25, 2019)
In: IEEE (ed.): 2019 IEEE International Conference on Image Processing (ICIP) 2019
DOI: 10.1109/ICIP.2019.8803116
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2019/Mayr19-WSS.pdf
BibTeX: Download
Hoffmann M., Doll B., Talkenberg F., Brabec C., Maier A., Christlein V.:
Fast and Robust Detection of Solar Modules in Electroluminescence Images
18th International Conference on Computer Analysis of Images and Patterns (Salerno, September 2, 2019 - September 6, 2019)
In: Springer, Cham (ed.): Computer Analysis of Images and Patterns 2019
DOI: 10.1007/978-3-030-29891-3
URL: https://www.researchgate.net/publication/335361806_Fast_and_Robust_Detection_of_Solar_Modules_in_Electroluminescence_Images
BibTeX: Download

2018

Journal Articles

Würfl T., Hoffmann M., Christlein V., Breininger K., Huang Y., Unberath M., Maier A.:
Deep Learning Computed Tomography: Learning Projection-Domain Weights from Image Domain in Limited Angle Problems
In: IEEE Transactions on Medical Imaging 37 (2018), p. 1454-1463
ISSN: 0278-0062
DOI: 10.1109/TMI.2018.2833499
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Wurfl18-DLC.pdf
BibTeX: Download

Conference Contributions

Hoffmann M., Würfl T., Maass N., Dennerlein F., Aichert A., Maier A.:
Empirical Scatter Correction using the Epipolar Consistency Condition
Fifth International Conference on Image Formation in X-Ray Computed Tomography (CT-Meeting) (Salt Lake City, USA)
In: Proceedings of the Fifth International Conference on Image Formation in X-Ray Computed Tomography (CT-Meeting) 2018
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Hoffmann18-ESC.pdf
BibTeX: Download

Student Thesis

Running:
No thesis found

Finnished:

Type	Title
MA thesis	Weakly supervised localization of defects in electroluminescence images of solar cells
BA thesis	Detection of Label Noise in Solar Cell Datasets
MA thesis	Solar Cell Aging Prediction using Deep Learning Image2Image Translation
MA thesis	Weakly-supervised segmentation of defects on solar cells
MA thesis	Using Deep Learning for segmentation of localized defects on SiC wafers
MA thesis	Learning From Weak Label Sources In Industrial Sensor Systems
MA thesis	Diagnosis of Gasoline Direct Injection Systems with Neural Networks
BA thesis	Semantic Segmentation of the Human Eye for Driver Monitoring
MA thesis	Multi-task Learning for Module Power Prediction and Failure Classification on EL Images
MA thesis	Automatic solar panel recognition, fault detection and localization in thermal images

Mathis Hoffmann, M. Sc.

CV CV

Projects Projects

2018

Analysis of Defects on Solar Power Cells

Publications Publications

2024

Journal Articles

2022

Journal Articles

2021

Journal Articles

Conference Contributions

2019

Journal Articles

Conference Contributions

2018

Journal Articles

Conference Contributions

Student Thesis Student Thesis

CV

Projects

Publications

Student Thesis