Suting Chen

1.3k citations
89 papers · 1.0k indexed · h-index 18

Impact in

Papers in

Suting Chen

84 papers receiving 994 citations

Peers

Suting Chen
Comparison fields: 5 of 143
  • Infectious Diseases 258
  • Media Technology 87
  • Epidemiology 247
  • Small Animals 51
  • Biological Psychiatry 17
Replace Yunjin Lee with:
Yunjin Lee South Korea
Aleksandra Tarkowska United Kingdom
Mark Anderson United States
Wei‐Yao Wang Taiwan
Rong Bao China
Luís G. Gonçalves Portugal
Xiaoyu Feng China
Jianwei Lu China
Penghao Wang Australia
M. Wada Japan
Suting Chen relative to Yunjin Lee South Korea Yunjin Lee's profile →
Citations per field
00.5×4.3×
Yunjin Lee · 1×
Citations per year

Countries citing papers authored by Suting Chen

Since Specialization
Citations

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

Fields of papers citing papers by Suting Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201992
2 201579
3 202059
4 201752
5 201145
6 201738
7 201530
8 200930
9 201830
10 202025
11 201523
12 202122
13 202221
14 201321
15 201618
16 201817
17 201017
18 202217
19 202216
20 201516

About Suting Chen

Suting Chen is a scholar working on Media Technology, Microbiology, Infectious Diseases, Computer Vision and Pattern Recognition and Small Animals, having authored 89 papers that have together received 1.0k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (22 papers), Mycobacterium research and diagnosis (17 papers), Advanced Image and Video Retrieval Techniques (9 papers), Video Surveillance and Tracking Methods (8 papers), Remote-Sensing Image Classification (7 papers), Remote Sensing and LiDAR Applications (6 papers), Advanced Neural Network Applications (5 papers) and Automated Road and Building Extraction (5 papers). The work is most often cited by research in Infectious Diseases (258 citations), Media Technology (87 citations), Epidemiology (247 citations), Small Animals (51 citations) and Biological Psychiatry (17 citations). Suting Chen has collaborated with scholars based in China, Canada and Australia. Frequent co-authors include Xiangdong Gao, Wenbing Yao, Hong Cai, Yan Sun, Jiayun Li, Song Chen, Hairong Huang, Rui Feng, Ying Wang and Jin Meng. Their work appears in journals such as Neurocomputing, Engineering Applications of Artificial Intelligence, Applied Intelligence, Acta Biochimica et Biophysica Sinica and Multimedia Tools and Applications.

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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