Peter Sinčák
Impact in
- Space and Planetary Science top 5%
- Archaeological Research and Protection
- Health Informatics top 10%
Papers in
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- Neural Networks and Applications 11
- Fuzzy Logic and Control Systems 7
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- Face and Expression Recognition 6
- Co-authors
- Ján Vaščák (10 shared papers)Filippo Cavallo (7 shared papers)Paolo Dario (2 shared papers)Laura Fiorini (2 shared papers)Francesco Semeraro (1 shared paper)Pitoyo Hartono (7 shared papers)Marián Mach (8 shared papers)Daniel Hládek (2 shared papers)
In The Last Decade
Peter Sinčák
70 papers receiving 768 citations
Peers
Comparison fields: 5 of 123
- Space and Planetary Science 32
- Health Informatics 18
- Computer Vision and Pattern Recognition 147
- Artificial Intelligence 228
- Control and Systems Engineering 156
Countries citing papers authored by Peter Sinčák
This map shows the geographic impact of Peter Sinčák'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 Sinčák with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Sinčák more than expected).
Fields of papers citing papers by Peter Sinčák
This network shows the impact of papers produced by Peter Sinčák. 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 Sinčák. The network helps show where Peter Sinčák may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Sinčák, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 187 | |
| 2 | 2018 | 89 | |
| 3 | 2020 | 58 | |
| 4 | 2019 | 48 | |
| 5 | 2020 | 38 | |
| 6 | 2005 | 24 | |
| 7 | 2008 | 21 | |
| 8 | 2013 | 19 | |
| 9 | Intelligent technologies - theory and applications : new trends in intelligent technologies | 2002 | 17 |
| 10 | 2018 | 17 | |
| 11 | 2014 | 17 | |
| 12 | 2014 | 14 | |
| 13 | 2018 | 14 | |
| 14 | 2021 | 12 | |
| 15 | 2013 | 12 | |
| 16 | 2019 | 10 | |
| 17 | 2019 | 10 | |
| 18 | 2004 | 10 | |
| 19 | 2016 | 10 | |
| 20 | 2017 | 9 |
About Peter Sinčák
Peter Sinčák is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Computer Networks and Communications and Social Psychology, having authored 74 papers that have together received 809 indexed citations. Recurring topics across this work include Robotics and Automated Systems (16 papers), Neural Networks and Applications (11 papers), Emotion and Mood Recognition (10 papers), Social Robot Interaction and HRI (9 papers), Fuzzy Logic and Control Systems (7 papers), Face and Expression Recognition (6 papers), IoT and Edge/Fog Computing (5 papers) and Robotics and Sensor-Based Localization (4 papers). The work is most often cited by research in Space and Planetary Science (32 citations), Health Informatics (18 citations), Computer Vision and Pattern Recognition (147 citations), Artificial Intelligence (228 citations) and Control and Systems Engineering (156 citations). Peter Sinčák has collaborated with scholars based in Slovakia, Japan and Italy. Frequent co-authors include Ján Vaščák, Filippo Cavallo, Paolo Dario, Laura Fiorini, Francesco Semeraro, Pitoyo Hartono, Marián Mach, Daniel Hládek, Xingfu Wang and Ammar Hawbani. Their work appears in journals such as IEEE Transactions on Fuzzy Systems, International Journal of Environmental Research and Public Health, Journal of Biomedical Informatics, Remote Sensing and Geocarto International.
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.