Roman Suvorov
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Computer Graphics and Computer-Aided Design top 2%
- Media Technology top 5%
- Computational Mechanics
- Co-authors
- Arsenii AshukhaElizaveta LogachevaNaejin KongHarshith GokaVictor LempitskyAleksandr I. PanovKonstantin YakovlevMeiyappan Nagappan
- Topics
- Topic Modeling (2 papers)Web Data Mining and Analysis (2 papers)Global Trade and Competitiveness (2 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionMedia Technology
- Journals
- Biochimica et Biophysica Acta (BBA) - Gene Regulatory MechanismsBulletin of Experimental Biology and MedicineForesight-Russia
- Partner nations
- RussiaSwitzerlandUnited States
In The Last Decade
Roman Suvorov
16 papers receiving 655 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 490
- Artificial Intelligence 107
- Computer Graphics and Computer-Aided Design 93
- Media Technology 59
- Computational Mechanics 45
Countries citing papers authored by Roman Suvorov
This map shows the geographic impact of Roman Suvorov'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 Roman Suvorov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roman Suvorov more than expected).
Fields of papers citing papers by Roman Suvorov
This network shows the impact of papers produced by Roman Suvorov. 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 Roman Suvorov. The network helps show where Roman Suvorov may publish in the future.
Co-authorship network of co-authors of Roman Suvorov
This figure shows the co-authorship network connecting the top 25 collaborators of Roman Suvorov. A scholar is included among the top collaborators of Roman Suvorov 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 Roman Suvorov. Roman Suvorov 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 | Resolution-robust Large Mask Inpainting with Fourier Convolutionsbreakdown → | 503 |
| 3 | 1 | |
| 4 | 8 | |
| 5 | 5 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 115 | |
| 9 | Towards Framework for Discovery of Export Growth Points. | 1 |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | 26 |
About Roman Suvorov
Roman Suvorov is a scholar working on General Economics, Econometrics and Finance, Information Systems and Geography, Planning and Development, having authored 17 papers that have together received 682 indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Web Data Mining and Analysis (2 papers) and Global Trade and Competitiveness (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (93 citations), Computer Vision and Pattern Recognition (490 citations) and Media Technology (59 citations). Roman Suvorov has collaborated with scholars based in Russia, Switzerland and United States. Frequent co-authors include Arsenii Ashukha, Elizaveta Logacheva, Naejin Kong, Harshith Goka, Victor Lempitsky, Aleksandr I. Panov, Konstantin Yakovlev, Meiyappan Nagappan, Bram Adams and Ahmed E. Hassan. Their work appears in journals such as Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, Bulletin of Experimental Biology and Medicine and Foresight-Russia.
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.