Kai Yan

528 citations
36 papers · 330 · h-index 9

Impact in

Papers in

Kai Yan

31 papers receiving 315 citations

Peers

Kai Yan
Comparison fields: 5 of 66
  • Computer Graphics and Computer-Aided Design 123
  • Computer Vision and Pattern Recognition 136
  • Computational Mechanics 90
  • Small Animals 29
  • Building and Construction 41
Replace Hiroshi Masuda with:
Hiroshi Masuda Japan
Guoyu Lu United States
Tong He China
Mathias Paulin France
Panagiotis Papadakis France
Ju He United States
Md Yushalify Misro Malaysia
Sung Heon Chung United States
Yohan Fougerolle France
Gokul Varadhan United States
Kai Yan relative to Hiroshi Masuda Japan Hiroshi Masuda's profile →
Citations per field
00.5×10×15×19.2×
Hiroshi Masuda · 1×
Citations per year

Countries citing papers authored by Kai Yan

Since Specialization
Citations

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

Fields of papers citing papers by Kai Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020104
2 202332
3 202228
4 200722
5 202220
6 202317
7 202213
8 202410
9 202210
10 20258
11 20098
12 20238
13 20236
14 20245
15 20245
16 20245
17 20084
18 20243
19 20243
20 20223

About Kai Yan

Kai Yan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Graphics and Computer-Aided Design, Electrical and Electronic Engineering and Civil and Structural Engineering, having authored 36 papers that have together received 330 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (7 papers), Advanced Vision and Imaging (6 papers), 3D Shape Modeling and Analysis (5 papers), Luminescence Properties of Advanced Materials (3 papers), Structural Behavior of Reinforced Concrete (3 papers), Structural Load-Bearing Analysis (2 papers), Cognitive Computing and Networks (2 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (123 citations), Computer Vision and Pattern Recognition (136 citations), Computational Mechanics (90 citations), Small Animals (29 citations) and Building and Construction (41 citations). Kai Yan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Shuang Zhao, Ioannis Gkioulekas, Cheng Zhang, Zhao Dong, Xin Zhang, Jeung‐Hwan Doh, Jiacheng Yang, Weizheng Shen, Xiangfeng Luo and Yanling Yin. Their work appears in journals such as Ceramics International, Computers and Electronics in Agriculture, IEEE Geoscience and Remote Sensing Letters, ACM Transactions on Graphics and Case Studies in Construction Materials.

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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