G. Ponimatkin
- Computer Vision and Pattern Recognition
- Control and Systems Engineering
- Nuclear and High Energy Physics
- Aerospace Engineering
- Biomedical Engineering
- Co-authors
- Thibault GroueixVincent LepetitTomáš HodaňI. LokhtinA. BelyaevMathieu SalzmannG. EyyubovaRenaud Marlet
- Topics
- High-Energy Particle Collisions Research (2 papers)Robot Manipulation and Learning (2 papers)Quantum Chromodynamics and Particle Interactions (2 papers)
- Cited by
- Nuclear and High Energy PhysicsComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- Journal of Physics G Nuclear and Particle PhysicsJournal of Experimental and Theoretical PhysicsInfoscience (Ecole Polytechnique Fédérale de Lausanne)
- Partner nations
- United StatesCzechiaFrance
In The Last Decade
G. Ponimatkin
4 papers receiving 35 citations
Peers
Comparison fields: 5 of 13
- Computer Vision and Pattern Recognition 16
- Control and Systems Engineering 13
- Nuclear and High Energy Physics 12
- Aerospace Engineering 9
- Biomedical Engineering 4
Countries citing papers authored by G. Ponimatkin
This map shows the geographic impact of G. Ponimatkin'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 G. Ponimatkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Ponimatkin more than expected).
Fields of papers citing papers by G. Ponimatkin
This network shows the impact of papers produced by G. Ponimatkin. 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 G. Ponimatkin. The network helps show where G. Ponimatkin may publish in the future.
Co-authorship network of co-authors of G. Ponimatkin
This figure shows the co-authorship network connecting the top 25 collaborators of G. Ponimatkin. A scholar is included among the top collaborators of G. Ponimatkin 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 G. Ponimatkin. G. Ponimatkin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 14 | |
| 3 | 6 | |
| 4 | 6 |
About G. Ponimatkin
G. Ponimatkin is a scholar working on Nuclear and High Energy Physics, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 4 papers that have together received 36 indexed citations. Recurring topics across this work include High-Energy Particle Collisions Research (2 papers), Robot Manipulation and Learning (2 papers) and Quantum Chromodynamics and Particle Interactions (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (12 citations), Computer Vision and Pattern Recognition (16 citations) and Control and Systems Engineering (13 citations). G. Ponimatkin has collaborated with scholars based in United States, Czechia and France. Frequent co-authors include Thibault Groueix, Vincent Lepetit, Tomáš Hodaň, I. Lokhtin, A. Belyaev, Mathieu Salzmann, G. Eyyubova, Renaud Marlet and Yinlin Hu. Their work appears in journals such as Journal of Physics G Nuclear and Particle Physics, Journal of Experimental and Theoretical Physics and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.