Mei Chen

569 citations
26 papers · 335 · h-index 8

Impact in

  • Biophysics top 5%
    • Cell Image Analysis Techniques
    • Image Retrieval and Classification Techniques
    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Human Pose and Action Recognition

Papers in

Mei Chen

25 papers receiving 326 citations

Peers

Mei Chen
Comparison fields: 5 of 74
  • Biophysics 108
  • Computer Vision and Pattern Recognition 160
  • Media Technology 56
  • Artificial Intelligence 117
  • Computer Science Applications 8
Replace Mahdi S. Hosseini with:
Mahdi S. Hosseini Canada
Riries Rulaningtyas Indonesia
Zhenyong Fu China
Shih-Fu Chang United States
Reza Hassanpour Türkiye
Dan Tu China
Eric Kee United States
Giorgos Sfikas Greece
Noura A. Semary Egypt
Mei Chen relative to Mahdi S. Hosseini Canada Mahdi S. Hosseini's profile →
Citations per field
00.5×3.6×
Mahdi S. Hosseini · 1×
Citations per year

Countries citing papers authored by Mei Chen

Since Specialization
Citations

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

Fields of papers citing papers by Mei Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201091
2 200850
3 200736
4 201933
5 201523
6 202223
7 199615
8 201914
9 20217
10 20107
11 20185
12 20134
13 20074
14 20103
15 20023
16 20253
17 20122
18 20202
19 20072
20 20242

About Mei Chen

Mei Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems and Signal Processing, having authored 26 papers that have together received 335 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Anomaly Detection Techniques and Applications (2 papers), Image Processing Techniques and Applications (2 papers), Software System Performance and Reliability (2 papers), Information Systems Education and Curriculum Development (2 papers), Teaching and Learning Programming (2 papers), Cell Image Analysis Techniques (2 papers) and Advanced Vision and Imaging (2 papers). The work is most often cited by research in Biophysics (108 citations), Computer Vision and Pattern Recognition (160 citations), Media Technology (56 citations), Artificial Intelligence (117 citations) and Computer Science Applications (8 citations). Mei Chen has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Takeo Kanade, Kang Li, Dai Fei Elmer Ker, Seungil Huh, Ryoma Bise, Eric D. Miller, Lee E. Weiss, Phil G. Campbell, Jing Zhang and Han Sun. Their work appears in journals such as Separation Science and Technology, IEEE Transactions on Medical Imaging, Neurocomputing, Knowledge-Based Systems and IEEE Transactions on Reliability.

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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