Václav Hlaváč
- Computer Vision and Pattern Recognition top 0.2%
- Artificial Intelligence top 2%
- Media Technology top 0.5%
- Biomedical Engineering top 10%
- Aerospace Engineering top 5%
- Co-authors
- Milan SonkaRoger BoyleVojtěch FrancChristian ThurauAlexander ShekhovtsovMichal UřičářDaniel PrůšaTomáš Pajdla
- Topics
- Advanced Vision and Imaging (10 papers)3D Shape Modeling and Analysis (10 papers)Robotics and Sensor-Based Localization (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Journals
- SHILAP Revista de lepidopterologíaMagnetic Resonance in MedicineSensors
- Partner nations
- CzechiaSlovakiaUnited Kingdom
In The Last Decade
Václav Hlaváč
78 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 189
- Computer Vision and Pattern Recognition 2.6k
- Artificial Intelligence 718
- Media Technology 474
- Biomedical Engineering 406
- Aerospace Engineering 371
Countries citing papers authored by Václav Hlaváč
This map shows the geographic impact of Václav Hlaváč'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 Václav Hlaváč with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Václav Hlaváč more than expected).
Fields of papers citing papers by Václav Hlaváč
This network shows the impact of papers produced by Václav Hlaváč. 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 Václav Hlaváč. The network helps show where Václav Hlaváč may publish in the future.
Co-authorship network of co-authors of Václav Hlaváč
This figure shows the co-authorship network connecting the top 25 collaborators of Václav Hlaváč. A scholar is included among the top collaborators of Václav Hlaváč 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 Václav Hlaváč. Václav Hlaváč is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 2 | |
| 6 | 26 | |
| 7 | 23 | |
| 8 | Interval Insensitive Loss for Ordinal Classification | 2 |
| 9 | 15 | |
| 10 | 11 | |
| 11 | 10 | |
| 12 | 203 | |
| 13 | 11 | |
| 14 | 10 | |
| 15 | 6 | |
| 16 | 2D context-free grammars: Mathematical formulae recognition. | 5 |
| 17 | 2 | |
| 18 | 68 | |
| 19 | Proceedings of the 27th Conference on Current Trends in Theory and Practice of Informatics | 2 |
| 20 | 1 |
About Václav Hlaváč
Václav Hlaváč is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Signal Processing, having authored 85 papers that have together received 4.4k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (10 papers), 3D Shape Modeling and Analysis (10 papers) and Robotics and Sensor-Based Localization (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.6k citations), Media Technology (474 citations) and Computer Graphics and Computer-Aided Design (119 citations). Václav Hlaváč has collaborated with scholars based in Czechia, Slovakia and United Kingdom. Frequent co-authors include Milan Sonka, Roger Boyle, Vojtěch Franc, Christian Thurau, Alexander Shekhovtsov, Michal Uřičář, Daniel Průša, Tomáš Pajdla, Pavel Kršek and Tomáš Svoboda. Their work appears in journals such as SHILAP Revista de lepidopterología, Magnetic Resonance in Medicine and Sensors.
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.