Shaokang Chen

1.0k total citations
53 papers, 487 citations indexed

About

Shaokang Chen is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Shaokang Chen has authored 53 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 17 papers in Electrical and Electronic Engineering and 7 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Shaokang Chen's work include Face and Expression Recognition (13 papers), Face recognition and analysis (11 papers) and Advanced Battery Materials and Technologies (7 papers). Shaokang Chen is often cited by papers focused on Face and Expression Recognition (13 papers), Face recognition and analysis (11 papers) and Advanced Battery Materials and Technologies (7 papers). Shaokang Chen collaborates with scholars based in China, Australia and Bulgaria. Shaokang Chen's co-authors include Brian C. Lovell, Conrad Sanderson, Abbas Bigdeli, Pengbo Liu, Huawei Zou, Sandra Mau, Long Ni, Mehrtash Harandi, Yinfu Luo and Xinyue Jiang and has published in prestigious journals such as PLoS ONE, IEEE Access and Journal of Materials Science.

In The Last Decade

Shaokang Chen

48 papers receiving 469 citations

Peers

Shaokang Chen
Comparison fields: 5 of 96
  • Computer Vision and Pattern Recognition 167
  • Electronic, Optical and Magnetic Materials 89
  • Electrical and Electronic Engineering 85
  • Aerospace Engineering 55
  • Materials Chemistry 50
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Citations per field, relative to Shaokang Chen
Shaokang Chen · 1×
Citations per year, relative to Shaokang Chen
Shaokang Chen · 1×

Countries citing papers authored by Shaokang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Shaokang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaokang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Shaokang Chen. A scholar is included among the top collaborators of Shaokang Chen 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 Shaokang Chen. Shaokang Chen 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 0
2 3
3 3
4 11
5 2
6 1
7 7
8 0
9 16
10 1
11 0
12 13
13 17
14 7
15 11
16 23
17 4
18 11
19
Face Recognition with One Sample Image per Class
2
20
Real-Time MMX-Accelerated Image Stabilization System
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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