Min Cao

743 total citations
28 papers, 553 citations indexed

About

Min Cao is a scholar working on Artificial Intelligence, Mechanical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Min Cao has authored 28 papers receiving a total of 553 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Mechanical Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Min Cao's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Asphalt Pavement Performance Evaluation (4 papers) and Non-Destructive Testing Techniques (4 papers). Min Cao is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Asphalt Pavement Performance Evaluation (4 papers) and Non-Destructive Testing Techniques (4 papers). Min Cao collaborates with scholars based in China, Hong Kong and France. Min Cao's co-authors include Dejin Zhang, Li He, Ying Chen, Bailing Zhang, Qingquan Li, Jingfu Wang, Xinxin Zhang, Peng Li, Junyu Liang and Jiuwen Cao and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Min Cao

27 papers receiving 527 citations

Peers

Min Cao
Comparison fields: 5 of 71
  • Civil and Structural Engineering 188
  • Mechanical Engineering 146
  • Artificial Intelligence 114
  • Computer Vision and Pattern Recognition 75
  • Atomic and Molecular Physics, and Optics 56
Amir Hossein Rezaie Iran
Thanh Sang-To Vietnam
Yibo Li China
Taeyong Kim South Korea
Ramin Ghiasi Ireland
Yuexin Zhang China
Zilong Zhang China
Wensheng Xiao China
Qingqing Xu China
Amir Hossein Rezaie Iran View profile →
Citations per field, relative to Min Cao
Min Cao · 1×
Citations per year, relative to Min Cao
Min Cao · 1×

Countries citing papers authored by Min Cao

Since Specialization
Citations

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

Fields of papers citing papers by Min Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Min Cao. A scholar is included among the top collaborators of Min Cao 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 Min Cao. Min Cao 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
# Work Indexed citations
1 16
2 9
3 0
4 51
5 10
6 24
7 3
8 2
9 1
10 44
11 7
12 2
13 40
14 30
15 126
16 4
17 2
18 2
19
Time series prediction for icing process of overhead power transmission line based on BP neural networks
11
20
Distributed Algorithms for Voronoi Diagrams and Applications in Ad-hoc Networks
16

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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