Zenon Kulpa
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Iwona SkalnaBjörn KruseSvetoslav MarkovRyszard S. MichalskiMichał KleiberMichael SobolewskiLeonard Bolc
- Topics
- Numerical Methods and Algorithms (8 papers)Digital Image Processing Techniques (6 papers)Constraint Satisfaction and Optimization (5 papers)
In The Last Decade
Zenon Kulpa
30 papers receiving 441 citations
Peers
Comparison fields: 5 of 93
- Computer Vision and Pattern Recognition 207
- Artificial Intelligence 116
- Computational Theory and Mathematics 91
- Computer Networks and Communications 77
- Experimental and Cognitive Psychology 55
Countries citing papers authored by Zenon Kulpa
This map shows the geographic impact of Zenon Kulpa'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 Zenon Kulpa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zenon Kulpa more than expected).
Fields of papers citing papers by Zenon Kulpa
This network shows the impact of papers produced by Zenon Kulpa. 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 Zenon Kulpa. The network helps show where Zenon Kulpa may publish in the future.
Co-authorship network of co-authors of Zenon Kulpa
This figure shows the co-authorship network connecting the top 25 collaborators of Zenon Kulpa. A scholar is included among the top collaborators of Zenon Kulpa 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 Zenon Kulpa. Zenon Kulpa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 22 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | Diagrammatic spreadsheet | 2 |
| 6 | 7 | |
| 7 | 8 | |
| 8 | Qualitative model-based analysis of truss structures | 1 |
| 9 | 24 | |
| 10 | Solution sets for systems of linear interval eguations | 6 |
| 11 | Characterization of convex and pointisable interval relations by diagrammatic methods | 5 |
| 12 | Analysis of linear mechanical structures with uncertainties by means of interval methods | 23 |
| 13 | 29 | |
| 14 | 3 | |
| 15 | DIAGRAMMATIC REPRESENTATION AND REASONING | 73 |
| 16 | 3 | |
| 17 | 36 | |
| 18 | 32 | |
| 19 | 1 | |
| 20 | 88 |
About Zenon Kulpa
Zenon Kulpa is a scholar working on Computer Graphics and Computer-Aided Design, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 519 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (8 papers), Digital Image Processing Techniques (6 papers) and Constraint Satisfaction and Optimization (5 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (52 citations), Computer Vision and Pattern Recognition (207 citations) and Computational Theory and Mathematics (91 citations). Zenon Kulpa has collaborated with scholars based in Poland, Bulgaria and Sweden. Frequent co-authors include Iwona Skalna, Björn Kruse, Svetoslav Markov, Ryszard S. Michalski, Michał Kleiber, Michael Sobolewski and Leonard Bolc. Their work appears in journals such as Signal Processing, Engineering Applications of Artificial Intelligence and Perception.
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.