Jin Yuan

48 total papers · 560 total citations
32 papers, 380 citations indexed

About

Jin Yuan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Jin Yuan has authored 32 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 5 papers in Media Technology. Recurrent topics in Jin Yuan's work include Video Surveillance and Tracking Methods (10 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Advanced Neural Network Applications (6 papers). Jin Yuan is often cited by papers focused on Video Surveillance and Tracking Methods (10 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Advanced Neural Network Applications (6 papers). Jin Yuan collaborates with scholars based in China, Hong Kong and Singapore. Jin Yuan's co-authors include Zhiyong Li, Yi Xiao, Weili Guan, Ke Nai, Meng Wang, Richang Hong, Da Cao, Xuan He, Ying Chen and Ying Chen and has published in prestigious journals such as IEEE Transactions on Image Processing, Expert Systems with Applications and IEEE Access.

In The Last Decade

Jin Yuan

29 papers receiving 373 citations

Author Peers

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

Author						Papers	Cites
Jin Yuan	262	106	43	30	28	32	380
Mohammad Kazem Moghimi	288 1.1×	175 1.7×	46 1.1×	28 0.9×	28 1.0×	21	443
Hamed Habibi Aghdam	199 0.8×	115 1.1×	77 1.8×	31 1.0×	26 0.9×	20	406
Luciano Oliveira	251 1.0×	98 0.9×	19 0.4×	43 1.4×	44 1.6×	41	395
Alok Kumar Singh Kushwaha	288 1.1×	117 1.1×	28 0.7×	25 0.8×	63 2.3×	57	372
Yunqi Lei	210 0.8×	51 0.5×	21 0.5×	40 1.3×	18 0.6×	45	336
Xuefeng Zhu	225 0.9×	100 0.9×	35 0.8×	72 2.4×	17 0.6×	37	393
Jie Liu	167 0.6×	147 1.4×	25 0.6×	26 0.9×	11 0.4×	31	367
Guoqing Jin	173 0.7×	125 1.2×	33 0.8×	30 1.0×	18 0.6×	32	416
Rin-ichiro Taniguchi	263 1.0×	67 0.6×	30 0.7×	56 1.9×	35 1.3×	39	391
Kaiqi Huang	341 1.3×	90 0.8×	70 1.6×	51 1.7×	20 0.7×	23	407

Countries citing papers authored by Jin Yuan

Since Specialization

Citations

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

Fields of papers citing papers by Jin Yuan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Yuan

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