Olga Barinova
- Computer Vision and Pattern Recognition top 5%
- Environmental Engineering top 10%
- Aerospace Engineering top 10%
- Geology top 5%
- Artificial Intelligence
- Co-authors
- Victor LempitskyPushmeet KohliРоман ШаповаловTatiana NovikovaAnna VorontsovaVladimir VezhnevetsV. GavrishchakaAlexander Vezhnevets
- Topics
- Advanced Image and Video Retrieval Techniques (4 papers)Remote Sensing and LiDAR Applications (4 papers)Image Retrieval and Classification Techniques (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionInternational Journal on Document Analysis and Recognition (IJDAR)
- Partner nations
- RussiaUnited KingdomUnited States
In The Last Decade
Olga Barinova
10 papers receiving 445 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 357
- Environmental Engineering 116
- Aerospace Engineering 107
- Geology 85
- Artificial Intelligence 72
Countries citing papers authored by Olga Barinova
This map shows the geographic impact of Olga Barinova'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 Olga Barinova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olga Barinova more than expected).
Fields of papers citing papers by Olga Barinova
This network shows the impact of papers produced by Olga Barinova. 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 Olga Barinova. The network helps show where Olga Barinova may publish in the future.
Co-authorship network of co-authors of Olga Barinova
This figure shows the co-authorship network connecting the top 25 collaborators of Olga Barinova. A scholar is included among the top collaborators of Olga Barinova 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 Olga Barinova. Olga Barinova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 39 | |
| 3 | 13 | |
| 4 | 43 | |
| 5 | 136 | |
| 6 | Online Random Forest for Interactive Image Segmentation | 2 |
| 7 | 69 | |
| 8 | NON-ASSOCIATIVE MARKOV NETWORKS FOR 3D POINT CLOUD CLASSIFICATION | 85 |
| 9 | 82 | |
| 10 | 1 | |
| 11 | Learning class specific edges for vanishing point estimation | 2 |
About Olga Barinova
Olga Barinova is a scholar working on Computer Vision and Pattern Recognition, Geology and Environmental Engineering, having authored 11 papers that have together received 473 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Remote Sensing and LiDAR Applications (4 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (357 citations), Geology (85 citations) and Environmental Engineering (116 citations). Olga Barinova has collaborated with scholars based in Russia, United Kingdom and United States. Frequent co-authors include Victor Lempitsky, Pushmeet Kohli, Роман Шаповалов, Tatiana Novikova, Anna Vorontsova, Vladimir Vezhnevets, V. Gavrishchaka, Alexander Vezhnevets and Anton Konushin. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and International Journal on Document Analysis and Recognition (IJDAR).
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.