Duo Wang

506 citations
27 papers · 345 · h-index 8

Impact in

Papers in

Duo Wang

24 papers receiving 327 citations

Peers

Duo Wang
Comparison fields: 5 of 76
  • Geometry and Topology 82
  • Computer Graphics and Computer-Aided Design 30
  • Statistical and Nonlinear Physics 61
  • Polymers and Plastics 60
  • Numerical Analysis 15
Replace Ciprian S. Borcea with:
Ciprian S. Borcea United States
Murray S. Klamkin Canada
Ludwig Danzer Germany
Károly Bezdek Hungary
Jörg Μ. Thuswaldner Austria
Mamikon A. Mnatsakanian United States
Abdul Rahman Abdullah Malaysia
Xiaohui Zhang China
Huaigu Tian China
Duo Wang relative to Ciprian S. Borcea United States Ciprian S. Borcea's profile →
Citations per field
00.5×10×15×
Ciprian S. Borcea · 1×
Citations per year

Countries citing papers authored by Duo Wang

Since Specialization
Citations

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

Fields of papers citing papers by Duo Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019113
2 199658
3 198645
4 201132
5 201023
6 202015
7 201113
8 20248
9 20166
10 20184
11 20204
12 20204
13 20123
14 20082
15 20202
16 20192
17 20222
18 20192
19
Fast Face Capturing and Tracking Method in Motion Image
20091
20
Centroid Detection of Targets on Near Infrared Stellar Map Based on C Spline Method and Gauss Method Comprision
20111

About Duo Wang

Duo Wang is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Electrical and Electronic Engineering, Control and Systems Engineering and Aerospace Engineering, having authored 27 papers that have together received 345 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (4 papers), Advanced Measurement and Detection Methods (3 papers), Infrared Target Detection Methodologies (3 papers), Image and Signal Denoising Methods (3 papers), Advanced Algorithms and Applications (2 papers), Differential Equations and Boundary Problems (2 papers), Manufacturing Process and Optimization (2 papers) and Computational Geometry and Mesh Generation (2 papers). The work is most often cited by research in Geometry and Topology (82 citations), Computer Graphics and Computer-Aided Design (30 citations), Statistical and Nonlinear Physics (61 citations), Polymers and Plastics (60 citations) and Numerical Analysis (15 citations). Duo Wang has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Xiangmin Jiao, Hiroshi Kokubu, Hiroe Oka, Toshihisa Tanaka, Zuqiang Bian, Zhijian Chen, Cuncun Wu, Ning Zhu, Shufeng Wang and Xuan Guo. Their work appears in journals such as Engineering With Computers, Optics Express, Electronics, IEEE Access and Journal of Computational Physics.

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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