Peter Drotár
Impact in
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
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- Handwritten Text Recognition Techniques
Papers in
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- Artificial Intelligence in Healthcare 16
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- Face and Expression Recognition 8
- Handwritten Text Recognition Techniques 7
- Co-authors
- Zdeněk Smékal (11 shared papers)Marcos Faúndez-Zanuy (7 shared papers)Jiří Mekyska (7 shared papers)Irena Rektorová (7 shared papers)Lucia Masárová (6 shared papers)Matej Gazda (15 shared papers)Liberios Vokorokos (5 shared papers)Juraj Gazda (18 shared papers)
In The Last Decade
Peter Drotár
62 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 103
- Health Information Management 691
- Computer Vision and Pattern Recognition 474
- Neurology 217
- Cognitive Neuroscience 298
- Physiology 319
Countries citing papers authored by Peter Drotár
This map shows the geographic impact of Peter Drotár'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 Peter Drotár with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Drotár more than expected).
Fields of papers citing papers by Peter Drotár
This network shows the impact of papers produced by Peter Drotár. 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 Peter Drotár. The network helps show where Peter Drotár may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Drotár, 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 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 270 | |
| 2 | 2014 | 154 | |
| 3 | 2014 | 124 | |
| 4 | 2021 | 108 | |
| 5 | 2019 | 86 | |
| 6 | 2020 | 85 | |
| 7 | 2018 | 78 | |
| 8 | 2015 | 69 | |
| 9 | 2022 | 69 | |
| 10 | 2021 | 64 | |
| 11 | 2013 | 59 | |
| 12 | 2019 | 58 | |
| 13 | 2021 | 58 | |
| 14 | 2021 | 56 | |
| 15 | 2013 | 53 | |
| 16 | 2018 | 42 | |
| 17 | 2015 | 39 | |
| 18 | 2018 | 27 | |
| 19 | 2023 | 22 | |
| 20 | 2021 | 21 |
About Peter Drotár
Peter Drotár is a scholar working on Health Information Management, Computer Vision and Pattern Recognition, Artificial Intelligence, Physiology and Statistics and Probability, having authored 66 papers that have together received 1.8k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (16 papers), Voice and Speech Disorders (12 papers), Face and Expression Recognition (8 papers), PAPR reduction in OFDM (8 papers), Handwritten Text Recognition Techniques (7 papers), Text and Document Classification Technologies (7 papers), Advanced Wireless Communication Techniques (7 papers) and Motor Control and Adaptation (7 papers). The work is most often cited by research in Health Information Management (691 citations), Computer Vision and Pattern Recognition (474 citations), Neurology (217 citations), Cognitive Neuroscience (298 citations) and Physiology (319 citations). Peter Drotár has collaborated with scholars based in Slovakia, Czechia and Spain. Frequent co-authors include Zdeněk Smékal, Marcos Faúndez-Zanuy, Jiří Mekyska, Irena Rektorová, Lucia Masárová, Matej Gazda, Liberios Vokorokos, Juraj Gazda, Dinesh Kumar and Nemuel Daniel Pah. Their work appears in journals such as Computer Methods and Programs in Biomedicine, PeerJ Computer Science, Computers in Biology and Medicine, Journal of Imaging Informatics in Medicine and Science China Information Sciences.
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.