Daniel Průša
Impact in
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- Handwritten Text Recognition Techniques
- Image Processing and 3D Reconstruction
- Advanced Image and Video Retrieval Techniques
Papers in
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- semigroups and automata theory 5
- Cellular Automata and Applications 4
- Advanced Graph Theory Research 4
- Complexity and Algorithms in Graphs 4
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- Algorithms and Data Compression 7
- Machine Learning and Algorithms 2
- Co-authors
- Václav Hlaváč (7 shared papers)Tomáš Werner (6 shared papers)Pavel Kršek (1 shared paper)Masaki Nakagawa (1 shared paper)František Mráz (4 shared papers)Vojtěch Franc (1 shared paper)Friedrich Otto (3 shared papers)Giovanni Pighizzini (2 shared papers)
In The Last Decade
Daniel Průša
25 papers receiving 169 citations
Peers
Comparison fields: 5 of 36
- Computer Vision and Pattern Recognition 94
- Computer Graphics and Computer-Aided Design 11
- Human-Computer Interaction 14
- Software 9
- Computational Theory and Mathematics 34
Countries citing papers authored by Daniel Průša
This map shows the geographic impact of Daniel Průša'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 Daniel Průša with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Průša more than expected).
Fields of papers citing papers by Daniel Průša
This network shows the impact of papers produced by Daniel Průša. 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 Daniel Průša. The network helps show where Daniel Průša may publish in the future.
Co-authors
The 9 scholars most cited alongside Daniel Průša, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 54 | |
| 2 | 2016 | 28 | |
| 3 | 2014 | 24 | |
| 4 | 2016 | 11 | |
| 5 | On discriminative learning of prediction uncertainty | 2019 | 7 |
| 6 | 2015 | 6 | |
| 7 | 2D context-free grammars: Mathematical formulae recognition. | 2006 | 5 |
| 8 | 2014 | 5 | |
| 9 | 2016 | 5 | |
| 10 | 2012 | 5 | |
| 11 | 2013 | 4 | |
| 12 | 2020 | 4 | |
| 13 | 2013 | 4 | |
| 14 | 2014 | 4 | |
| 15 | 2015 | 3 | |
| 16 | On a class of rational functions for pictures. | 2015 | 2 |
| 17 | Web application for recognition of mathematical formulas. | 2011 | 2 |
| 18 | 2015 | 2 | |
| 19 | 2016 | 1 | |
| 20 | 2017 | 1 |
About Daniel Průša
Daniel Průša is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology and Computer Networks and Communications, having authored 26 papers that have together received 182 indexed citations. Recurring topics across this work include Algorithms and Data Compression (7 papers), DNA and Biological Computing (7 papers), Handwritten Text Recognition Techniques (6 papers), semigroups and automata theory (5 papers), Cellular Automata and Applications (4 papers), Advanced Graph Theory Research (4 papers), Complexity and Algorithms in Graphs (4 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (94 citations), Computer Graphics and Computer-Aided Design (11 citations), Human-Computer Interaction (14 citations), Software (9 citations) and Computational Theory and Mathematics (34 citations). Daniel Průša has collaborated with scholars based in Czechia, Germany and Italy. Frequent co-authors include Václav Hlaváč, Tomáš Werner, Pavel Kršek, Masaki Nakagawa, František Mráz, Vojtěch Franc, Friedrich Otto, Giovanni Pighizzini and Klaus Reinhardt. Their work appears in journals such as Information and Computation, Theoretical Computer Science, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Foundations of Computer Science and SIAM Journal on Optimization.
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.