Maja Krivokuća

22 total papers · 941 total citations
14 papers, 653 citations indexed

About

Maja Krivokuća is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Maja Krivokuća has authored 14 papers receiving a total of 653 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 9 papers in Computational Mechanics and 9 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Maja Krivokuća's work include 3D Shape Modeling and Analysis (9 papers), Computer Graphics and Visualization Techniques (9 papers) and Advanced Vision and Imaging (8 papers). Maja Krivokuća is often cited by papers focused on 3D Shape Modeling and Analysis (9 papers), Computer Graphics and Visualization Techniques (9 papers) and Advanced Vision and Imaging (8 papers). Maja Krivokuća collaborates with scholars based in United States, France and New Zealand. Maja Krivokuća's co-authors include Philip A. Chou, Robert Cohen, Madhukar Budagavi, Pablo César, Zhu Li, Marius Preda, Joan Llach, Alexis M. Tourapis, Rufael Mekuria and Vittorio Baroncini and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Multimedia and IEEE Signal Processing Letters.

In The Last Decade

Maja Krivokuća

12 papers receiving 638 citations

Hit Papers

Emerging MPEG Standards f... 2018 2026 2020 2023 2018 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maja Krivokuća 487 397 366 111 96 14 653
Sébastien Lasserre 411 0.8× 303 0.8× 292 0.8× 88 0.8× 84 0.9× 8 559
Khaled Mammou 466 1.0× 370 0.9× 346 0.9× 100 0.9× 92 1.0× 5 619
Ernestasia Siahaan 483 1.0× 301 0.8× 276 0.8× 86 0.8× 139 1.4× 17 719
Joan Llach 530 1.1× 295 0.7× 284 0.8× 85 0.8× 110 1.1× 21 687
Vladyslav Zakharchenko 639 1.3× 379 1.0× 362 1.0× 101 0.9× 133 1.4× 8 789
Vittorio Baroncini 631 1.3× 297 0.7× 282 0.8× 85 0.8× 206 2.1× 24 779
Sven Woop 518 1.1× 316 0.8× 601 1.6× 44 0.4× 70 0.7× 21 779
Xavier Décoret 501 1.0× 298 0.8× 570 1.6× 75 0.7× 15 0.2× 20 708
Vitaly Surazhsky 283 0.6× 500 1.3× 480 1.3× 22 0.2× 30 0.3× 14 781
Manfred Ernst 379 0.8× 177 0.4× 316 0.9× 41 0.4× 40 0.4× 14 577

Countries citing papers authored by Maja Krivokuća

Since Specialization
Citations

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

Fields of papers citing papers by Maja Krivokuća

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maja Krivokuća. 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 Maja Krivokuća. The network helps show where Maja Krivokuća may publish in the future.

Co-authorship network of co-authors of Maja Krivokuća

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

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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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