Lutz Priese
- Computer Vision and Pattern Recognition top 10%
- Computational Theory and Mathematics top 5%
- Media Technology top 10%
- Artificial Intelligence
- Molecular Biology
- Co-authors
- Paul A. LemkePhilippe DarondeauMaurice MargensternAldo von WangenheimMichael M. RichterCristian S. CaludeAntonio Carlos SobieranskiHaojun Wang
- Topics
- semigroups and automata theory (8 papers)Image Retrieval and Classification Techniques (7 papers)Medical Image Segmentation Techniques (6 papers)
In The Last Decade
Lutz Priese
31 papers receiving 222 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 119
- Computational Theory and Mathematics 85
- Media Technology 49
- Artificial Intelligence 45
- Molecular Biology 37
Countries citing papers authored by Lutz Priese
This map shows the geographic impact of Lutz Priese'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 Lutz Priese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lutz Priese more than expected).
Fields of papers citing papers by Lutz Priese
This network shows the impact of papers produced by Lutz Priese. 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 Lutz Priese. The network helps show where Lutz Priese may publish in the future.
Co-authorship network of co-authors of Lutz Priese
This figure shows the co-authorship network connecting the top 25 collaborators of Lutz Priese. A scholar is included among the top collaborators of Lutz Priese based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lutz Priese. Lutz Priese is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | Automatische See-Through Kalibrierung | 11 |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 30 | |
| 7 | 20 | |
| 8 | 9 | |
| 9 | Finite H-systems with 3 test tubes are not predictable. | 5 |
| 10 | Disjunctive Sequences: An Overview | 3 |
| 11 | Fairness, part II. | 0 |
| 12 | 0 | |
| 13 | 6 | |
| 14 | 4 | |
| 15 | 11 | |
| 16 | 6 | |
| 17 | 2 | |
| 18 | 10 | |
| 19 | 13 | |
| 20 | 7 |
About Lutz Priese
Lutz Priese is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Media Technology, having authored 35 papers that have together received 243 indexed citations. Recurring topics across this work include semigroups and automata theory (8 papers), Image Retrieval and Classification Techniques (7 papers) and Medical Image Segmentation Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (119 citations), Media Technology (49 citations) and Computational Theory and Mathematics (85 citations). Lutz Priese has collaborated with scholars based in Germany, Canada and Brazil. Frequent co-authors include Paul A. Lemke, Philippe Darondeau, Maurice Margenstern, Aldo von Wangenheim, Michael M. Richter, Cristian S. Calude, Antonio Carlos Sobieranski, Haojun Wang, Katrin Erk and Irène Guessarian. Their work appears in journals such as Pattern Recognition Letters, SIAM Journal on Computing and Theoretical Computer Science.
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.