Pavel Mrázek⋆

981 citations
8 papers · 496 indexed · h-index 6
Topics
Image and Signal Denoising Methods (7 papers)Medical Image Segmentation Techniques (3 papers)Seismic Imaging and Inversion Techniques (2 papers)
Partner nations
GermanyCzechia

In The Last Decade

Pavel Mrázek⋆

8 papers receiving 461 citations

Peers

Pavel Mrázek⋆
Comparison fields: 5 of 61
  • Computer Vision and Pattern Recognition 396
  • Media Technology 124
  • Computational Mechanics 120
  • Radiology, Nuclear Medicine and Imaging 48
  • Mathematical Physics 45
Replace Triet Le with:
Triet Le United States
Andrés Solé Spain
Martin Welk Germany
Miyoun Jung South Korea
Carole Le Guyader France
François Malgouyres France
Leah Bar Israel
Stamatios Lefkimmiatis Switzerland
Frédéric Cao France
Luca Calatroni France
Pavel Mrázek⋆ relative to Triet Le United States Triet Le's profile →
Citations per field
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Citations per year

Countries citing papers authored by Pavel Mrázek⋆

Since Specialization
Citations

This map shows the geographic impact of Pavel Mrázek⋆'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 Pavel Mrázek⋆ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavel Mrázek⋆ more than expected).

Fields of papers citing papers by Pavel Mrázek⋆

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pavel Mrázek⋆. 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 Pavel Mrázek⋆. The network helps show where Pavel Mrázek⋆ may publish in the future.

Co-authorship network of co-authors of Pavel Mrázek⋆

This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Mrázek⋆. A scholar is included among the top collaborators of Pavel Mrázek⋆ 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 Pavel Mrázek⋆. Pavel Mrázek⋆ is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1 23
2 165
3 26
4 158
5
On Iterations and Scales of Nonlinear Filters
10
6 106
7 3
8
Consistent Positive Directional Splitting of Anisotropic Diusion
5

About Pavel Mrázek⋆

Pavel Mrázek⋆ is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics and Geophysics, having authored 8 papers that have together received 496 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (7 papers), Medical Image Segmentation Techniques (3 papers) and Seismic Imaging and Inversion Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (396 citations), Media Technology (124 citations) and Computational Mathematics (5 citations). Pavel Mrázek⋆ has collaborated with scholars based in Germany and Czechia. Frequent co-authors include Joachim Weickert, Thomas Brox, Mirko Navara, Bernhard Burgeth, Martin Welk, Gabriele Steidl, Gabriele Steidl and Gabriele Steidl. Their work appears in journals such as International Journal of Computer Vision, SIAM Journal on Numerical Analysis and Image and Vision Computing.

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.

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