Réka Hollandi
- Biophysics top 5%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Péter HorváthNikita MoshkovAttila Kertész‐FarkasErvin TasnádiFilippo PiccininiLassi PaavolainenTobias M. RasseEdit Hermesz
- Topics
- Cell Image Analysis Techniques (5 papers)Image Processing Techniques and Applications (3 papers)Digital Imaging for Blood Diseases (2 papers)
In The Last Decade
Réka Hollandi
9 papers receiving 244 citations
Peers
Comparison fields: 5 of 87
- Biophysics 83
- Computer Vision and Pattern Recognition 82
- Artificial Intelligence 77
- Molecular Biology 43
- Radiology, Nuclear Medicine and Imaging 43
Countries citing papers authored by Réka Hollandi
This map shows the geographic impact of Réka Hollandi'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 Réka Hollandi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Réka Hollandi more than expected).
Fields of papers citing papers by Réka Hollandi
This network shows the impact of papers produced by Réka Hollandi. 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 Réka Hollandi. The network helps show where Réka Hollandi may publish in the future.
Co-authorship network of co-authors of Réka Hollandi
This figure shows the co-authorship network connecting the top 25 collaborators of Réka Hollandi. A scholar is included among the top collaborators of Réka Hollandi 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 Réka Hollandi. Réka Hollandi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 44 | |
| 3 | 13 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 27 | |
| 7 | 134 | |
| 8 | 13 | |
| 9 | 8 | |
| 10 | 5 |
About Réka Hollandi
Réka Hollandi is a scholar working on Biophysics, Media Technology and Computer Vision and Pattern Recognition, having authored 10 papers that have together received 248 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (5 papers), Image Processing Techniques and Applications (3 papers) and Digital Imaging for Blood Diseases (2 papers). The work is most often cited by research in Biophysics (83 citations), Computer Vision and Pattern Recognition (82 citations) and Media Technology (34 citations). Réka Hollandi has collaborated with scholars based in Hungary, Finland and Russia. Frequent co-authors include Péter Horváth, Nikita Moshkov, Attila Kertész‐Farkas, Ervin Tasnádi, Filippo Piccinini, Lassi Paavolainen, Tobias M. Rasse, Edit Hermesz, Pavel Horváth and Lukas Badertscher. Their work appears in journals such as Nucleic Acids Research, Scientific Reports and Small.
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.