Chén Mĭn

12 papers receiving 286 citations

Peers

Chén Mĭn
Comparison fields: 5 of 84
  • Computer Vision and Pattern Recognition 114
  • Safety, Risk, Reliability and Quality 50
  • Computer Graphics and Computer-Aided Design 18
  • Information Systems and Management 23
  • Medical Laboratory Technology 5
Replace Reza Ravanmehr with:
Reza Ravanmehr Iran
Hasan Yetış Türkiye
John Griffith United States
Xiaoya Zhang China
Shogo Nishida Japan
Yingyu Chen China
Chen Guo China
Supeno Mardi Susiki Nugroho Indonesia
Zeeshan Bhatti Pakistan
Chén Mĭn relative to Reza Ravanmehr Iran Reza Ravanmehr's profile →
Citations per field
00.5×
Reza Ravanmehr · 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 201095
2 202067
3 201832
4 201126
5 201225
6 201321
7 201515
8 200810
9 20193
10
SPEED AND TENDENCY OF CHINA’S URBANIZATION: COMPARATIVE STUDY BASED ON CROSS-COUNTRY PANEL DATA MODEL
20132
11 20211
12 20221
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 298 indexed citations. Recurring topics across this work include Data Visualization and Analytics (3 papers), Magnetism in coordination complexes (2 papers), Caching and Content Delivery (2 papers), Lanthanide and Transition Metal Complexes (2 papers), Electron Spin Resonance Studies (2 papers), Video Analysis and Summarization (2 papers), Recommender Systems and Techniques (2 papers) and Web Data Mining and Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (114 citations), Safety, Risk, Reliability and Quality (50 citations), Computer Graphics and Computer-Aided Design (18 citations), Information Systems and Management (23 citations) and Medical Laboratory Technology (5 citations). Chén Mĭn has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Hongpeng Yin, Young U. Ryu, Luciano Floridi, Varghese S. Jacob, Jim Davies, Eamonn Maguire, Susanna‐Assunta Sansone, Suresh Radhakrishnan, Philippe Rocca‐Serra and Ross Maciejewski. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Knowledge and Data Engineering, CrystEngComm, Reliability Engineering & System Safety and Decision Support Systems.

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.

Explore authors with similar magnitude of impact