Di‐Rong Chen

1.3k citations
76 papers · 1.0k · h-index 17

Impact in

Papers in

Di‐Rong Chen

67 papers receiving 956 citations

Peers

Di‐Rong Chen
Comparison fields: 5 of 106
  • Computational Mechanics 462
  • Computer Vision and Pattern Recognition 341
  • Acoustics and Ultrasonics 13
  • Applied Mathematics 147
  • Mathematical Physics 120
Replace Shao-Bo Lin with:
Shao-Bo Lin China
Greg Knowles United Kingdom
Xiangyu Chang China
Avraham A. Melkman Israel
Gill Barequet Israel
Zongben Xu China
Oswin Aichholzer Austria
Lifeng Wang China
Juan Andrés Bazerque United States
I. D. Coope New Zealand
Di‐Rong Chen relative to Shao-Bo Lin China Shao-Bo Lin's profile →
Citations per field
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Shao-Bo Lin · 1×
Citations per year

Countries citing papers authored by Di‐Rong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Di‐Rong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Support Vector Machine Soft Margin Classifiers: Error Analysis
2004185
2 201277
3 201469
4 200259
5 200851
6 201337
7 201535
8 200034
9 200733
10 201330
11 201529
12 201027
13 200023
14 201021
15 200821
16 201821
17 200916
18 200615
19 201614
20 201711

About Di‐Rong Chen

Di‐Rong Chen is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Mathematical Physics, Applied Mathematics and Artificial Intelligence, having authored 76 papers that have together received 1.0k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (28 papers), Numerical methods in inverse problems (17 papers), Statistical Methods and Inference (14 papers), Image and Signal Denoising Methods (12 papers), Mathematical Analysis and Transform Methods (11 papers), Face and Expression Recognition (10 papers), Advanced Numerical Analysis Techniques (10 papers) and Control Systems and Identification (9 papers). The work is most often cited by research in Computational Mechanics (462 citations), Computer Vision and Pattern Recognition (341 citations), Acoustics and Ultrasonics (13 citations), Applied Mathematics (147 citations) and Mathematical Physics (120 citations). Di‐Rong Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ding‐Xuan Zhou, Qiang Wu, Yiming Ying, Rui Wu, Yongli Xu, Lu Liu, S. D. Riemenschneider, Wei Huang, Lizhong Peng and Rong-Qing Jia. Their work appears in journals such as Journal of Approximation Theory, Journal of Mathematical Analysis and Applications, Applied and Computational Harmonic Analysis, Journal of Statistical Planning and Inference and Journal of Inequalities 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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