Chun Guan

842 citations
52 papers · 596 · h-index 11

Impact in

Papers in

Chun Guan

49 papers receiving 562 citations

Peers

Chun Guan
Comparison fields: 5 of 92
  • Computer Vision and Pattern Recognition 371
  • Media Technology 127
  • Geology 79
  • Instrumentation 39
  • Mechanical Engineering 124
Replace Qun Wu with:
Qun Wu China
Dehong Yu China
Hao Pan China
Jingbo Zhang China
Shan Jiang China
Hoon Yoo South Korea
Tao Yan China
Haiyang Huang China
Lixin Shi United States
Gaurav Parmar United States
Chun Guan relative to Qun Wu China Qun Wu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Chun Guan

Since Specialization
Citations

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

Fields of papers citing papers by Chun Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003168
2 2003152
3 202342
4 201836
5 202318
6 202015
7 201512
8 202311
9 201310
10 202410
11 200810
12 20248
13 20067
14 20236
15 20046
16 20156
17 20085
18 20165
19 20175
20 20244

About Chun Guan

Chun Guan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Information Systems and Computer Networks and Communications, having authored 52 papers that have together received 596 indexed citations. Recurring topics across this work include Optical measurement and interference techniques (7 papers), Advanced Memory and Neural Computing (6 papers), 3D Surveying and Cultural Heritage (5 papers), Neural Networks and Reservoir Computing (5 papers), Advanced Clustering Algorithms Research (5 papers), Recommender Systems and Techniques (5 papers), Complex Network Analysis Techniques (5 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (371 citations), Media Technology (127 citations), Geology (79 citations), Instrumentation (39 citations) and Mechanical Engineering (124 citations). Chun Guan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Laurence G. Hassebrook, Daniel L. Lau, Jielin Li, Kevin Kam Fung Yuen, Siyang Leng, Frans Coenen, Zhongxue Gan, Ruizhi Cao, Jin Hui Shi and Qi Chen. Their work appears in journals such as Optics & Laser Technology, European Journal of Medicinal Chemistry, Pattern Recognition, Applied Physics Letters and Swarm and Evolutionary Computation.

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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