Chén Mĭn

12 papers receiving 319 citations

Peers

Chén Mĭn
Comparison fields: 5 of 84
  • Computer Vision and Pattern Recognition 128
  • Safety, Risk, Reliability and Quality 50
  • Computer Graphics and Computer-Aided Design 19
  • Medical Laboratory Technology 6
  • Information Systems and Management 29
Replace Syed M Rahman with:
Syed M Rahman United States
Hasan Yetış Türkiye
Myunggwon Hwang South Korea
Reza Ravanmehr Iran
Xiaoya Zhang China
Rakesh Mehta Finland
Zeeshan Bhatti Pakistan
John Griffith United States
Juhee Bae Sweden
Chén Mĭn relative to Syed M Rahman United States Syed M Rahman's profile →
Citations per field
00.5×5×10×16.7×
Syed M Rahman · 1×
Citations per year

Countries citing papers authored by Chén Mĭn

Since Specialization
Citations

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

Fields of papers citing papers by Chén Mĭn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Chén Mĭn, 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 Chén Mĭn Line = papers co-authored together Chén Mĭn links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2010105
2 202069
3 201838
4 201232
5 201129
6 201325
7 201517
8 200811
9 20194
10
SPEED AND TENDENCY OF CHINA’S URBANIZATION: COMPARATIVE STUDY BASED ON CROSS-COUNTRY PANEL DATA MODEL
20132
11 20221
12 20211
13 20230
14 20180

About Chén Mĭn

Chén Mĭn is a scholar working on Computer Vision and Pattern Recognition, Information Systems, Information Systems and Management, Biophysics and Computer Networks and Communications, having authored 14 papers that have together received 334 indexed citations. Recurring topics across this work include Data Visualization and Analytics (3 papers), Electron Spin Resonance Studies (2 papers), Lanthanide and Transition Metal Complexes (2 papers), Web Data Mining and Analysis (2 papers), Recommender Systems and Techniques (2 papers), Magnetism in coordination complexes (2 papers), Video Analysis and Summarization (2 papers) and Caching and Content Delivery (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (128 citations), Safety, Risk, Reliability and Quality (50 citations), Computer Graphics and Computer-Aided Design (19 citations), Medical Laboratory Technology (6 citations) and Information Systems and Management (29 citations). Chén Mĭn has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Young U. Ryu, Hongpeng Yin, Luciano Floridi, Eamonn Maguire, Susanna‐Assunta Sansone, Philippe Rocca‐Serra, Jim Davies, Suresh Radhakrishnan, Varghese S. Jacob and David S. Ebert. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Knowledge and Data Engineering, CrystEngComm, Synthese and Information Systems Research.

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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