Zsolt Kira

206 total papers · 5.6k total citations
68 papers, 1.8k citations indexed

About

Zsolt Kira is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Zsolt Kira has authored 68 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Vision and Pattern Recognition, 40 papers in Artificial Intelligence and 11 papers in Aerospace Engineering. Recurrent topics in Zsolt Kira's work include Domain Adaptation and Few-Shot Learning (23 papers), Multimodal Machine Learning Applications (22 papers) and Advanced Neural Network Applications (15 papers). Zsolt Kira is often cited by papers focused on Domain Adaptation and Few-Shot Learning (23 papers), Multimodal Machine Learning Applications (22 papers) and Advanced Neural Network Applications (15 papers). Zsolt Kira collaborates with scholars based in United States, Germany and Canada. Zsolt Kira's co-authors include Chih‐Yao Ma, Ghassan AlRegib, Yen‐Cheng Liu, Chia-Wen Kuo, Junjiao Tian, Min-Hung Chen, Jingdao Chen, Yong K. Cho, James Smith and Yen-Chang Hsu and has published in prestigious journals such as SAE technical papers on CD-ROM/SAE technical paper series, IEEE Robotics and Automation Letters and Journal of Computing in Civil Engineering.

In The Last Decade

Zsolt Kira

61 papers receiving 1.8k citations

Hit Papers

CODA-Prompt: COntinual De... 2023 2026 2024 2023 25 50 75

Author Peers

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

Author Last Decade Papers Cites
Zsolt Kira 1.2k 753 239 152 150 68 1.8k
Yang Zhang 948 0.8× 284 0.4× 260 1.1× 134 0.9× 124 0.8× 98 1.9k
Xinyi Le 615 0.5× 462 0.6× 145 0.6× 331 2.2× 217 1.4× 67 1.9k
Ahmad Jalal 1.3k 1.1× 363 0.5× 159 0.7× 78 0.5× 73 0.5× 86 2.0k
Du Q. Huynh 1.3k 1.1× 479 0.6× 281 1.2× 173 1.1× 87 0.6× 79 2.0k
Jihua Zhu 1.2k 1.0× 550 0.7× 429 1.8× 141 0.9× 156 1.0× 153 1.9k
Christian Plagemann 803 0.7× 444 0.6× 400 1.7× 306 2.0× 57 0.4× 35 1.6k
John Zelek 913 0.8× 263 0.3× 336 1.4× 67 0.4× 116 0.8× 152 1.4k
Hongkai Yu 1.3k 1.1× 424 0.6× 194 0.8× 130 0.9× 39 0.3× 82 1.9k
James Ferryman 1.8k 1.6× 658 0.9× 213 0.9× 48 0.3× 44 0.3× 112 2.3k
Kai Sun 617 0.5× 304 0.4× 232 1.0× 192 1.3× 45 0.3× 94 1.4k

Countries citing papers authored by Zsolt Kira

Since Specialization
Citations

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

Fields of papers citing papers by Zsolt Kira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zsolt Kira

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

All Works

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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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