Ping Lü

115 papers receiving 1.4k citations

Peers

Ping Lü
Comparison fields: 5 of 153
  • Computer Vision and Pattern Recognition 292
  • Artificial Intelligence 383
  • Spectroscopy 157
  • Radiology, Nuclear Medicine and Imaging 209
  • Computational Mechanics 182
Replace B. Michael Kelm with:
B. Michael Kelm Germany
Feng Yang China
Rachid Jennane France
Ying Xue China
Nilanjan Ray Canada
Yuemin Zhu France
Michael Kühn Germany
Ping Xue China
Jun Suzuki Japan
M. Iqbal Saripan Malaysia
Ping Lü relative to B. Michael Kelm Germany B. Michael Kelm's profile →
Citations per field
00.5×7.9×
B. Michael Kelm · 1×
Citations per year

Countries citing papers authored by Ping Lü

Since Specialization
Citations

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

Fields of papers citing papers by Ping Lü

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995131
2 2018124
3 202255
4
Prevalence of pre-eruptive intracoronal dentin defects from panoramic radiographs.
199951
5 200850
6 202148
7 202247
8 202439
9 202339
10 201038
11 199334
12 202029
13 201327
14 202225
15 202324
16 199523
17 201723
18 202221
19 201021
20 198718

About Ping Lü

Ping Lü is a scholar working on Computer Vision and Pattern Recognition, Filtration and Separation, Computational Mechanics, Artificial Intelligence and Signal Processing, having authored 128 papers that have together received 1.4k indexed citations. Recurring topics across this work include Fluid Dynamics and Turbulent Flows (10 papers), Spectroscopy and Laser Applications (8 papers), Speech and Audio Processing (8 papers), Advanced Image and Video Retrieval Techniques (7 papers), Advanced Data Storage Technologies (6 papers), Speech Recognition and Synthesis (6 papers), Advanced Neural Network Applications (5 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (292 citations), Artificial Intelligence (383 citations), Spectroscopy (157 citations), Radiology, Nuclear Medicine and Imaging (209 citations) and Computational Mechanics (182 citations). Ping Lü has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jincai Chen, Maryellen L. Giger, Min Chen, Chao Yang, Zhimin Huo, Carl J. Vyborny, Chaoqun Liu, Zai‐Sha Mao, Ulrich Bick and Andrej Košir. Their work appears in journals such as Photoacoustics, IEEE Transactions on Magnetics, Sensors, Journal of Chemical & Engineering Data and Optics Express.

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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