Zhenkun Lu

27 papers receiving 308 citations

Peers

Zhenkun Lu
Comparison fields: 5 of 69
  • Computer Vision and Pattern Recognition 82
  • Health Informatics 5
  • Neurology 27
  • Artificial Intelligence 103
  • Mechanics of Materials 72
Replace Sergiy Sadovnychiy with:
Sergiy Sadovnychiy Mexico
Lidong Yang China
Qingzeng Song China
M.W. Roth United States
Zhe Jiang China
Toshihiko Nishimura Japan
Qianqian Du China
Ronald L. Allen United States
Mathilde Mougeot France
Xiaoyong Zhang Japan
Zhenkun Lu relative to Sergiy Sadovnychiy Mexico Sergiy Sadovnychiy's profile →
Citations per field
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Sergiy Sadovnychiy · 1×
Citations per year

Countries citing papers authored by Zhenkun Lu

Since Specialization
Citations

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

Fields of papers citing papers by Zhenkun Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202350
2 202342
3 202337
4 201630
5 202015
6 202214
7 201514
8 202013
9 202013
10 202312
11 202311
12 20119
13 20157
14 20226
15 20146
16 20234
17 20204
18 20253
19 20233
20 20243

About Zhenkun Lu

Zhenkun Lu is a scholar working on Computer Vision and Pattern Recognition, Mechanics of Materials, Signal Processing, Artificial Intelligence and Electrical and Electronic Engineering, having authored 29 papers that have together received 314 indexed citations. Recurring topics across this work include Ultrasonics and Acoustic Wave Propagation (7 papers), Flow Measurement and Analysis (6 papers), Image and Signal Denoising Methods (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Blind Source Separation Techniques (2 papers), Biometric Identification and Security (2 papers), Spacecraft Dynamics and Control (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (82 citations), Health Informatics (5 citations), Neurology (27 citations), Artificial Intelligence (103 citations) and Mechanics of Materials (72 citations). Zhenkun Lu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Qinghua Huang, Longzhong Liu, Wei Wang, Donghong Qin, Yuling Luo, Yaozhong Luo, Shichong Zhou, Cai Chang, Jiawei Li and Moe Momayez. Their work appears in journals such as Advances in Space Research, Signal Processing, Measurement, Biomedical Signal Processing and Control and Expert Systems with 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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