Shaoyan Gai

714 citations
49 papers · 542 indexed · h-index 15
Topics
Optical measurement and interference techniques (30 papers)Advanced Vision and Imaging (14 papers)Image Processing Techniques and Applications (14 papers)

In The Last Decade

Shaoyan Gai

40 papers receiving 507 citations

Peers

Shaoyan Gai
Comparison fields: 5 of 62
  • Computer Vision and Pattern Recognition 421
  • Media Technology 169
  • Mechanical Engineering 135
  • Geology 95
  • Electrical and Electronic Engineering 83
Replace Christophe Stolz with:
Christophe Stolz France
S. Inokuchi Japan
Haiyang Mei China
Masanori Idesawa Japan
Heinz Hügli Switzerland
Hongbo Bi China
Jinhong Xu China
Michael Van den Bergh Switzerland
Kenkichi Yamamoto Japan
David Hafner Germany
Shaoyan Gai relative to Christophe Stolz France Christophe Stolz's profile →
Citations per field
00.5×3.3×
Christophe Stolz · 1×
Citations per year

Countries citing papers authored by Shaoyan Gai

Since Specialization
Citations

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

Fields of papers citing papers by Shaoyan Gai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaoyan Gai

This figure shows the co-authorship network connecting the top 25 collaborators of Shaoyan Gai. A scholar is included among the top collaborators of Shaoyan Gai 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 Shaoyan Gai. Shaoyan Gai 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
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4 1
5 0
6 2
7 1
8 1
9 1
10 7
11 19
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13 22
14 20
15 34
16
Multi-cameras calibration approach based on fringe projection
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17 6
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Color structured light technology for high-speed 3D shape measurement based on gray code method
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19 22
20 52

About Shaoyan Gai

Shaoyan Gai is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Geology, having authored 49 papers that have together received 542 indexed citations. Recurring topics across this work include Optical measurement and interference techniques (30 papers), Advanced Vision and Imaging (14 papers) and Image Processing Techniques and Applications (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (421 citations), Media Technology (169 citations) and Geology (95 citations). Shaoyan Gai has collaborated with scholars based in China, Bangladesh and United States. Frequent co-authors include Feipeng Da, Lin Huang, Dingcai Cao, Wenlong Chen, Ming Tang, Wenjian Li, Lulu Zeng, Damber Thapa, Fang Xu and Yiming Lu. Their work appears in journals such as PLoS ONE, IEEE Transactions on Image Processing and Optics Letters.

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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