Chao Yuan

507 citations
51 papers · 329 indexed · h-index 11
Topics
Face and Expression Recognition (14 papers)Machine Learning and ELM (7 papers)Neural Networks and Applications (5 papers)
Journals
SHILAP Revista de lepidopterologíaInternational Journal of Heat and Mass TransferIEEE Access
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Chao Yuan

47 papers receiving 318 citations

Peers

Chao Yuan
Comparison fields: 5 of 72
  • Artificial Intelligence 147
  • Computer Vision and Pattern Recognition 94
  • Control and Systems Engineering 63
  • Electrical and Electronic Engineering 46
  • Aerospace Engineering 40
Replace Langming Liu with:
Langming Liu China
Miaomiao Zhang China
Taifan Quan China
Xi’an Feng China
Mary M. Moya United States
W. Ahmed United States
Rifat Edizkan Türkiye
Daw-Ran Liou Taiwan
Yulai Cong China
Yunfei Guo China
Chao Yuan relative to Langming Liu China Langming Liu's profile →
Citations per field
00.5×2.7×
Langming Liu · 1×
Citations per year

Countries citing papers authored by Chao Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Chao Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chao Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Chao Yuan. A scholar is included among the top collaborators of Chao 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 Chao Yuan. Chao Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
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4 1
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7 2
8 20
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10 25
11 5
12 7
13 11
14 12
15
Variational Mixture of Gaussian Process Experts
40
16 3
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20 10

About Chao Yuan

Chao Yuan is a scholar working on Energy Engineering and Power Technology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 51 papers that have together received 329 indexed citations. Recurring topics across this work include Face and Expression Recognition (14 papers), Machine Learning and ELM (7 papers) and Neural Networks and Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (94 citations), Artificial Intelligence (147 citations) and Media Technology (34 citations). Chao Yuan has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Liming Yang, David Casasent, Jun Ma, Ping Sun, Yichen Tian, Jiaxiang Zheng, Feifei Zhang, Dongming Li, Xiangjun Zeng and Yuan Mao. Their work appears in journals such as SHILAP Revista de lepidopterología, International Journal of Heat and Mass Transfer and IEEE Access.

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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