Jun Yan

2.9k citations
81 papers · 1.7k · h-index 25

Impact in

Papers in

Jun Yan

77 papers receiving 1.6k citations

Peers

Jun Yan
Comparison fields: 5 of 146
  • Artificial Intelligence 918
  • Computational Mathematics 15
  • Health Informatics 27
  • Computer Vision and Pattern Recognition 389
  • Information Systems 325
Replace Tong Xu with:
Tong Xu China
Fabio Aiolli Italy
Andreas Kanavos Greece
Max Chickering United States
Sungchul Kim United States
Fang Han United States
Aleksandra Mojsilović United States
Lin Li China
Zeno Gantner Germany
Praveen Paritosh United States
Jun Yan relative to Tong Xu China Tong Xu's profile →
Citations per field
00.5×10×15.6×
Tong Xu · 1×
Citations per year

Countries citing papers authored by Jun Yan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Yan Line = papers co-authored together Jun Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020172
2 2006131
3 2007102
4 201990
5 201881
6 200566
7 200861
8 200856
9 202045
10 201044
11 202043
12 200643
13 200441
14 201840
15 201532
16 202131
17 200928
18 201727
19 201027
20 201426

About Jun Yan

Jun Yan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Sociology and Political Science and Marketing, having authored 81 papers that have together received 1.7k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (19 papers), Topic Modeling (17 papers), Web Data Mining and Analysis (11 papers), Face and Expression Recognition (9 papers), Image Retrieval and Classification Techniques (9 papers), Natural Language Processing Techniques (8 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Digital Marketing and Social Media (6 papers). The work is most often cited by research in Artificial Intelligence (918 citations), Computational Mathematics (15 citations), Health Informatics (27 citations), Computer Vision and Pattern Recognition (389 citations) and Information Systems (325 citations). Jun Yan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Benyu Zhang, Shuicheng Yan, Tianyong Hao, Qiang Yang, Xieling Chen, Weiguo Fan, Buzhou Tang, Zheng Chen, Qiansheng Cheng and Zheng Chen. Their work appears in journals such as BMC Medical Informatics and Decision Making, International Journal of Security and Networks, IEEE Transactions on Knowledge and Data Engineering, Journal of Medical Internet Research and Journal of the Association for Information Science and Technology.

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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