Shengyang Dai

27 total papers · 1.3k total citations
15 papers, 829 citations indexed

About

Shengyang Dai is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Shengyang Dai has authored 15 papers receiving a total of 829 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 6 papers in Media Technology and 3 papers in Artificial Intelligence. Recurrent topics in Shengyang Dai's work include Advanced Image Processing Techniques (8 papers), Image Processing Techniques and Applications (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Shengyang Dai is often cited by papers focused on Advanced Image Processing Techniques (8 papers), Image Processing Techniques and Applications (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Shengyang Dai collaborates with scholars based in United States and China. Shengyang Dai's co-authors include Ying Wu, Mei Han, Yihong Gong, Ying Wu, Aggelos K. Katsaggelos, Wei Xu, Qingmin Liao, Yihong Gong, Ying Wu and Ming Yang and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition Letters and 2009 IEEE Conference on Computer Vision and Pattern Recognition.

In The Last Decade

Shengyang Dai

15 papers receiving 787 citations

Author Peers

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

Author Last Decade Papers Cites
Shengyang Dai 792 419 83 47 41 15 829
T. Chang 801 1.0× 326 0.8× 124 1.5× 27 0.6× 35 0.9× 8 1.0k
Wei Wang 691 0.9× 349 0.8× 48 0.6× 38 0.8× 36 0.9× 11 916
Keyan Ding 632 0.8× 253 0.6× 76 0.9× 16 0.3× 21 0.5× 22 871
Won-Dong Jang 845 1.1× 302 0.7× 89 1.1× 59 1.3× 10 0.2× 29 1.0k
Mark Thurston 511 0.6× 142 0.3× 79 1.0× 36 0.8× 31 0.8× 16 742
Dennis F. Dunn 609 0.8× 212 0.5× 88 1.1× 13 0.3× 36 0.9× 12 815
P. Kruizinga 606 0.8× 219 0.5× 152 1.8× 43 0.9× 18 0.4× 17 926
Jiangxin Dong 703 0.9× 430 1.0× 36 0.4× 13 0.3× 29 0.7× 24 803
Junru Wu 824 1.0× 304 0.7× 81 1.0× 9 0.2× 14 0.3× 10 946
Zudi Lin 461 0.6× 459 1.1× 55 0.7× 45 1.0× 24 0.6× 13 780

Countries citing papers authored by Shengyang Dai

Since Specialization
Citations

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

Fields of papers citing papers by Shengyang Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shengyang Dai

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