Ping Yan

42 papers receiving 983 citations

Peers

Ping Yan
Comparison fields: 5 of 85
  • Signal Processing 443
  • Computer Vision and Pattern Recognition 501
  • Industrial and Manufacturing Engineering 141
  • Medical Laboratory Technology 7
  • Information Systems 102
Replace Yu Ding with:
Yu Ding China
Tong Yu China
Ziyan Wu United States
Yongwan Park South Korea
Usman Habib Pakistan
N. Ruiz-Reyes Spain
Daniela Sánchez Mexico
Francescomaria Marino Italy
Yifan Guo United States
Daeyoung Kim South Korea
Ping Yan relative to Yu Ding China Yu Ding's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ping Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ping Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007251
2 200696
3 201763
4 200649
5 201347
6 200644
7 201741
8 200640
9 200531
10 200628
11 200728
12 201726
13 202124
14 200622
15 201522
16 200521
17
Ear biometrics in human identification
200620
18 202218
19 200715
20 202114

About Ping Yan

Ping Yan is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Signal Processing, Mechanical Engineering and Biomedical Engineering, having authored 45 papers that have together received 1.0k indexed citations. Recurring topics across this work include Biometric Identification and Security (10 papers), Manufacturing Process and Optimization (8 papers), Face recognition and analysis (8 papers), Machine Fault Diagnosis Techniques (6 papers), Reconstructive Facial Surgery Techniques (5 papers), Industrial Vision Systems and Defect Detection (5 papers), Elasticity and Material Modeling (4 papers) and Advanced machining processes and optimization (4 papers). The work is most often cited by research in Signal Processing (443 citations), Computer Vision and Pattern Recognition (501 citations), Industrial and Manufacturing Engineering (141 citations), Medical Laboratory Technology (7 citations) and Information Systems (102 citations). Ping Yan has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Kevin W. Bowyer, Albert J. Sinusas, James S. Duncan, Yan He, Yan Wang, Karl Thiele, Yufeng Li, Han Zhou, Murray K. Clayton and Jun Zhu. Their work appears in journals such as Advanced Engineering Informatics, Medical Image Analysis, Journal of Intelligent Manufacturing, The International Journal of Advanced Manufacturing Technology and Engineering Failure Analysis.

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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