Michael Fauser
Impact in
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- Industrial Vision Systems and Defect Detection
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
Papers in
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- Anomaly Detection Techniques and Applications 4
- Domain Adaptation and Few-Shot Learning 1
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- Digital Media Forensic Detection 2
- Advanced Neural Network Applications 1
- Advanced Image and Video Retrieval Techniques 1
- Video Surveillance and Tracking Methods 1
- Co-authors
- Paul Bergmann (5 shared papers)Carsten Steger (5 shared papers)David Sattlegger (5 shared papers)Sindy Löwe (1 shared paper)Simone Warzel (1 shared paper)
- Journals
- International Journal of Computer Vision (2 papers)Reviews in Mathematical Physics (1 paper)Lecture notes in computer science (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- GermanyNetherlands
In The Last Decade
Michael Fauser
7 papers receiving 2.3k citations
Michael Fauser's Hit Papers
Peers
Comparison fields: 5 of 97
- Industrial and Manufacturing Engineering 716
- Artificial Intelligence 1.8k
- Computer Vision and Pattern Recognition 637
- Computer Networks and Communications 525
- Signal Processing 178
Countries citing papers authored by Michael Fauser
This map shows the geographic impact of Michael Fauser's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Fauser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Fauser more than expected).
Fields of papers citing papers by Michael Fauser
This network shows the impact of papers produced by Michael Fauser. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Fauser. The network helps show where Michael Fauser may publish in the future.
Co-authors
The 5 scholars most cited alongside Michael Fauser, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection Hit paper breakdown → | 2019 | 1090 |
| 2 | Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings Hit paper breakdown → | 2020 | 572 |
| 3 | The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection Hit paper breakdown → | 2021 | 308 |
| 4 | 2019 | 209 | |
| 5 | 2022 | 123 | |
| 6 | 2015 | 8 | |
| 7 | 2017 | 7 |
About Michael Fauser
Michael Fauser is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Molecular Biology and Mathematical Physics, having authored 7 papers that have together received 2.3k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Industrial Vision Systems and Defect Detection (3 papers), Digital Media Forensic Detection (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Quantum chaos and dynamical systems (1 paper), Advanced Neural Network Applications (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Video Surveillance and Tracking Methods (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (716 citations), Artificial Intelligence (1.8k citations), Computer Vision and Pattern Recognition (637 citations), Computer Networks and Communications (525 citations) and Signal Processing (178 citations). Michael Fauser has collaborated with scholars based in Germany and Netherlands. Frequent co-authors include Paul Bergmann, Carsten Steger, David Sattlegger, Sindy Löwe and Simone Warzel. Their work appears in journals such as International Journal of Computer Vision, Reviews in Mathematical Physics, Lecture notes in computer science and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.