Benyue Su

82 total papers · 754 total citations
52 papers, 541 citations indexed

About

Benyue Su is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Benyue Su has authored 52 papers receiving a total of 541 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 11 papers in Biomedical Engineering and 8 papers in Artificial Intelligence. Recurrent topics in Benyue Su's work include Human Pose and Action Recognition (8 papers), Image and Signal Denoising Methods (6 papers) and Advanced Numerical Analysis Techniques (5 papers). Benyue Su is often cited by papers focused on Human Pose and Action Recognition (8 papers), Image and Signal Denoising Methods (6 papers) and Advanced Numerical Analysis Techniques (5 papers). Benyue Su collaborates with scholars based in China, Poland and Australia. Benyue Su's co-authors include Jing Jiang, Min Sheng, Jie Wang, Shuangqing Liu, Kui Xiang, Fei Han, Qing-Hua Ling, Jian Wu, Jing Li and Xu Zhang and has published in prestigious journals such as IEEE Access, Lab on a Chip and Information Sciences.

In The Last Decade

Benyue Su

44 papers receiving 534 citations

Author Peers

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

Author Last Decade Papers Cites
Benyue Su 188 139 105 82 53 52 541
Muhammad Umer Khan 112 0.6× 83 0.6× 95 0.9× 88 1.1× 23 0.4× 53 566
Xiang Gao 253 1.3× 44 0.3× 111 1.1× 124 1.5× 61 1.2× 41 528
Qun Wu 130 0.7× 176 1.3× 24 0.2× 98 1.2× 14 0.3× 33 481
Mengyuan Li 61 0.3× 176 1.3× 74 0.7× 79 1.0× 74 1.4× 42 618
Konrad Wojciechowski 106 0.6× 187 1.3× 44 0.4× 59 0.7× 18 0.3× 75 514
Hongsheng He 130 0.7× 194 1.4× 92 0.9× 120 1.5× 4 0.1× 65 617
Shuai Li 45 0.2× 67 0.5× 197 1.9× 117 1.4× 12 0.2× 40 568
Weiming Wang 101 0.5× 194 1.4× 148 1.4× 85 1.0× 24 0.5× 37 575
Nursabillilah Mohd Ali 85 0.5× 149 1.1× 42 0.4× 126 1.5× 14 0.3× 52 470
Dan Wang 70 0.4× 106 0.8× 15 0.1× 74 0.9× 26 0.5× 51 502

Countries citing papers authored by Benyue Su

Since Specialization
Citations

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

Fields of papers citing papers by Benyue Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benyue Su

This figure shows the co-authorship network connecting the top 25 collaborators of Benyue Su. A scholar is included among the top collaborators of Benyue Su 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 Benyue Su. Benyue Su 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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