Yan Jin

49 papers receiving 436 citations

Peers

Yan Jin
Comparison fields: 5 of 66
  • Computer Networks and Communications 207
  • Discrete Mathematics and Combinatorics 28
  • Media Technology 45
  • Computer Vision and Pattern Recognition 102
  • Computational Mathematics 2
Replace Yoon Mo Jung with:
Yoon Mo Jung South Korea
Yubo Li China
Chung Shue Chen France
Shanxiang Lyu China
Jason C. Tillett United States
Emma Regentova United States
Cong Lin China
G. Umamaheswari India
Efi Fogel Israel
Mahmoud Melkemi France
Yan Jin relative to Yoon Mo Jung South Korea Yoon Mo Jung's profile →
Citations per field
00.5×10×13×
Yoon Mo Jung · 1×
Citations per year

Countries citing papers authored by Yan Jin

Since Specialization
Citations

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

Fields of papers citing papers by Yan Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yan Jin, 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 Yan Jin Line = papers co-authored together Yan Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007105
2 200936
3 202031
4 200829
5 201922
6 202020
7 201917
8 201216
9 201915
10 201814
11 200913
12 202213
13 20189
14 20118
15 20078
16 20198
17 20158
18 20066
19 20176
20 20115

About Yan Jin

Yan Jin is a scholar working on Computer Networks and Communications, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Discrete Mathematics and Combinatorics, having authored 56 papers that have together received 458 indexed citations. Recurring topics across this work include Advanced Graph Theory Research (16 papers), Energy Efficient Wireless Sensor Networks (10 papers), Mobile Ad Hoc Networks (10 papers), Image and Signal Denoising Methods (9 papers), Limits and Structures in Graph Theory (9 papers), Advanced Image Processing Techniques (6 papers), Graph theory and applications (6 papers) and Energy Harvesting in Wireless Networks (5 papers). The work is most often cited by research in Computer Networks and Communications (207 citations), Discrete Mathematics and Combinatorics (28 citations), Media Technology (45 citations), Computer Vision and Pattern Recognition (102 citations) and Computational Mathematics (2 citations). Yan Jin has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Yoohwan Kim, Ling Wang, Xiaozong Yang, Xiaoben Jiang, Ju-Yeon Jo, Guofang Wang, Yu Yao, Jürgen Jost, David I Shuman and Yingtao Jiang. Their work appears in journals such as The Visual Computer, Journal of Visual Communication and Image Representation, Graphs and Combinatorics, Discrete Applied Mathematics and Journal of Graph Theory.

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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