Kai Jin

658 total citations
27 papers, 418 citations indexed

About

Kai Jin is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Signal Processing. According to data from OpenAlex, Kai Jin has authored 27 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 5 papers in Electrical and Electronic Engineering and 3 papers in Signal Processing. Recurrent topics in Kai Jin's work include Face recognition and analysis (5 papers), Video Surveillance and Tracking Methods (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Kai Jin is often cited by papers focused on Face recognition and analysis (5 papers), Video Surveillance and Tracking Methods (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Kai Jin collaborates with scholars based in China, United States and United Kingdom. Kai Jin's co-authors include Xiuzhuang Zhou, Guodong Guo, Yuanyuan Shang, Min Xu, Liang-Hui Wang, Jueqi Guan, Gwo‐Jen Hwang, Weiwei Cui, Yuxiao Guo and Huamin Qu and has published in prestigious journals such as Advanced Functional Materials, Water Research and Scientific Reports.

In The Last Decade

Kai Jin

24 papers receiving 408 citations

Peers

Kai Jin
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 170
  • Experimental and Cognitive Psychology 163
  • Artificial Intelligence 68
  • Social Psychology 62
  • Cognitive Neuroscience 55
Replace Paweł Tarnowski with:
Paweł Tarnowski Poland
Xinlei Li China
Elena Di Lascio Switzerland
A. M. Mutawa Kuwait
Isabelle Hupont Spain
Norhaslinda Kamaruddin Malaysia
Thibaud Sénéchal United States
Kun-Yi Huang Taiwan
Shkurta Gashi Switzerland
Mirela Popa Netherlands
Paweł Tarnowski Poland View profile →
Citations per field, relative to Kai Jin
Kai Jin · 1×
Citations per year, relative to Kai Jin
Kai Jin · 1×

Countries citing papers authored by Kai Jin

Since Specialization
Citations

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

Fields of papers citing papers by Kai Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Jin. A scholar is included among the top collaborators of Kai Jin 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 Kai Jin. Kai Jin 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 1
2 1
3 7
4 7
5 1
6 4
7 19
8 0
9 1
10 1
11 51
12 3
13 0
14 56
15 3
16 1
17 5
18 4
19 10
20 1

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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