David Sattlegger
Impact in
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- Industrial Vision Systems and Defect Detection
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications
Papers in
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- Anomaly Detection Techniques and Applications 6
- Adversarial Robustness in Machine Learning 1
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- Industrial Vision Systems and Defect Detection 4
- Co-authors
- Paul Bergmann (7 shared papers)Carsten Steger (6 shared papers)Michael Fauser (5 shared papers)Sindy Löwe (1 shared paper)Xin Jin (1 shared paper)
- Journals
- International Journal of Computer Vision (2 papers)2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- GermanyNetherlands
In The Last Decade
David Sattlegger
7 papers receiving 2.0k citations
David Sattlegger's Hit Papers
Peers
Comparison fields: 5 of 92
- Industrial and Manufacturing Engineering 685
- Artificial Intelligence 1.6k
- Computer Vision and Pattern Recognition 584
- Computer Networks and Communications 448
- Media Technology 137
Countries citing papers authored by David Sattlegger
This map shows the geographic impact of David Sattlegger'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 David Sattlegger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Sattlegger more than expected).
Fields of papers citing papers by David Sattlegger
This network shows the impact of papers produced by David Sattlegger. 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 David Sattlegger. The network helps show where David Sattlegger may publish in the future.
Co-authors
The 5 scholars most cited alongside David Sattlegger, 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 | 938 |
| 2 | Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings Hit paper breakdown → | 2020 | 489 |
| 3 | The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection Hit paper breakdown → | 2021 | 251 |
| 4 | 2019 | 187 | |
| 5 | 2022 | 97 | |
| 6 | 2022 | 83 | |
| 7 | 2023 | 42 |
About David Sattlegger
David Sattlegger is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition, Molecular Biology and Media Technology, having authored 7 papers that have together received 2.1k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Industrial Vision Systems and Defect Detection (4 papers), Digital Media Forensic Detection (2 papers), Bacillus and Francisella bacterial research (1 paper), Remote Sensing and LiDAR Applications (1 paper), Image and Object Detection Techniques (1 paper), 3D Surveying and Cultural Heritage (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (685 citations), Artificial Intelligence (1.6k citations), Computer Vision and Pattern Recognition (584 citations), Computer Networks and Communications (448 citations) and Media Technology (137 citations). David Sattlegger has collaborated with scholars based in Germany and Netherlands. Frequent co-authors include Paul Bergmann, Carsten Steger, Michael Fauser, Sindy Löwe and Xin Jin. Their work appears in journals such as International Journal of Computer Vision, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 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.