Vladimír Ulman
- Biophysics top 5%
- Molecular Biology
- Cell Biology
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- David SvobodaMichal KozubekMiroslav VařechaMichal ZimmermannEmı́lie LukášováIgor PeterlíkPavel TomančákStefan Münster
- Topics
- Cell Image Analysis Techniques (10 papers)Advanced Fluorescence Microscopy Techniques (8 papers)Single-cell and spatial transcriptomics (4 papers)
In The Last Decade
Vladimír Ulman
20 papers receiving 203 citations
Peers
Comparison fields: 5 of 68
- Biophysics 82
- Molecular Biology 80
- Cell Biology 52
- Biomedical Engineering 30
- Computer Vision and Pattern Recognition 29
Countries citing papers authored by Vladimír Ulman
This map shows the geographic impact of Vladimír Ulman'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 Vladimír Ulman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladimír Ulman more than expected).
Fields of papers citing papers by Vladimír Ulman
This network shows the impact of papers produced by Vladimír Ulman. 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 Vladimír Ulman. The network helps show where Vladimír Ulman may publish in the future.
Co-authorship network of co-authors of Vladimír Ulman
This figure shows the co-authorship network connecting the top 25 collaborators of Vladimír Ulman. A scholar is included among the top collaborators of Vladimír Ulman 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 Vladimír Ulman. Vladimír Ulman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 53 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 19 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 18 | |
| 9 | 25 | |
| 10 | 4 | |
| 11 | 4 | |
| 12 | 2 | |
| 13 | 10 | |
| 14 | 4 | |
| 15 | Arbitrarily-oriented anisotropic 3D Gaussian filtering computed with 1D convolutions without interpolation | 1 |
| 16 | 33 | |
| 17 | 7 | |
| 18 | 3 | |
| 19 | Estimating Large Local Motion in Live-Cell Imaging UsingVariational Optical Flow | 4 |
| 20 | [Acquiring images with very high resolution using a composing method]. | 1 |
About Vladimír Ulman
Vladimír Ulman is a scholar working on Biophysics, Media Technology and Computer Graphics and Computer-Aided Design, having authored 20 papers that have together received 204 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (10 papers), Advanced Fluorescence Microscopy Techniques (8 papers) and Single-cell and spatial transcriptomics (4 papers). The work is most often cited by research in Biophysics (82 citations), Cell Biology (52 citations) and Media Technology (24 citations). Vladimír Ulman has collaborated with scholars based in Czechia, Germany and Russia. Frequent co-authors include David Svoboda, Michal Kozubek, Miroslav Vařecha, Michal Zimmermann, Emı́lie Lukášová, Igor Peterlík, Pavel Tomančák, Stefan Münster, Pavel Matula and Stephan W. Grill. Their work appears in journals such as Nature Communications, IEEE Transactions on Medical Imaging and Medical Image Analysis.
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.