Yeping Peng

2.5k total citations · 1 hit paper
67 papers, 1.9k citations indexed

About

Yeping Peng is a scholar working on Mechanical Engineering, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yeping Peng has authored 67 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Mechanical Engineering, 15 papers in Electrical and Electronic Engineering and 14 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yeping Peng's work include Lubricants and Their Additives (16 papers), Industrial Vision Systems and Defect Detection (12 papers) and Machine Fault Diagnosis Techniques (7 papers). Yeping Peng is often cited by papers focused on Lubricants and Their Additives (16 papers), Industrial Vision Systems and Defect Detection (12 papers) and Machine Fault Diagnosis Techniques (7 papers). Yeping Peng collaborates with scholars based in China, Australia and Vietnam. Yeping Peng's co-authors include Ngaiming Kwok, Tonghai Wu, Zhongxiao Peng, Hongkun Wu, Xingjian Jing, Marjan Goodarzi, Guang‐Zhong Cao, Baowei Wang, Hongkun Wu and Su‐Dan Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Hydrogen Energy and IEEE Access.

In The Last Decade

Yeping Peng

59 papers receiving 1.8k citations

Hit Papers

Damage detection techniques for wind turbine blades: A re... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yeping Peng China 25 796 351 330 265 264 67 1.9k
Maolin Cai China 26 1.2k 1.5× 287 0.8× 284 0.9× 158 0.6× 309 1.2× 194 2.4k
H. Metin Ertunç Türkiye 26 1.4k 1.8× 469 1.3× 446 1.4× 232 0.9× 703 2.7× 79 2.6k
Jianguo Yang China 26 937 1.2× 534 1.5× 521 1.6× 56 0.2× 365 1.4× 118 2.0k
Dong Jiang China 26 804 1.0× 199 0.6× 233 0.7× 128 0.5× 333 1.3× 167 2.1k
Liping Wang China 30 1.6k 2.0× 869 2.5× 241 0.7× 414 1.6× 1.4k 5.4× 174 2.9k
Panorios Benardos Greece 13 1.4k 1.8× 527 1.5× 756 2.3× 592 2.2× 100 0.4× 34 1.9k
Hong Bao China 25 454 0.6× 262 0.7× 223 0.7× 87 0.3× 505 1.9× 108 1.6k
Kai Guo China 32 2.1k 2.6× 588 1.7× 515 1.6× 281 1.1× 635 2.4× 131 2.7k
Yongqing Wang China 19 591 0.7× 225 0.6× 120 0.4× 74 0.3× 101 0.4× 107 1.0k
Haiou Zhang China 31 2.8k 3.5× 240 0.7× 448 1.4× 496 1.9× 75 0.3× 116 4.0k

Countries citing papers authored by Yeping Peng

Since Specialization
Citations

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

Fields of papers citing papers by Yeping Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yeping Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Yeping Peng. A scholar is included among the top collaborators of Yeping Peng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yeping Peng. Yeping Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wu, Chao, et al.. (2025). Multi-step prediction of greenhouse crop growth based on the SVR_Seq2Seq model. Smart Agricultural Technology. 11. 100986–100986. 1 indexed citations
2.
Peng, Yeping, et al.. (2025). Binocular-Separated Modeling for Efficient Binocular Stereo Matching. IEEE Transactions on Intelligent Transportation Systems. 26(3). 3028–3038.
3.
Peng, Yeping, et al.. (2025). Uniformity and stability of saliva composition based on glucose concentration analysis. Clinica Chimica Acta. 573. 120283–120283.
4.
Peng, Yeping, et al.. (2024). Three-dimensional reconstruction of wear particle surfaces using multi-focus image sequence. Measurement. 235. 114925–114925.
5.
Wang, Zihao, Jian Song, & Yeping Peng. (2024). New insights and perspectives into biodegradable metals in cardiovascular stents: A mini review. Journal of Alloys and Compounds. 1002. 175313–175313. 15 indexed citations
6.
Peng, Yeping, Deyu Kong, Song Wang, Guang‐Zhong Cao, & Chaozong Liu. (2024). In-Vitro Investigation on the Tribological Properties of Nickel-Titanium (NiTi) Alloy Used in Braided Vascular Stents. Tribology Transactions. 67(5). 1002–1015. 2 indexed citations
7.
Peng, Yeping, et al.. (2023). Point Cloud Registration Based on Fast Point Feature Histogram Descriptors for 3D Reconstruction of Trees. Remote Sensing. 15(15). 3775–3775. 13 indexed citations
8.
Peng, Yeping, et al.. (2023). Study on wear debris characteristics of different polyethylene under reciprocating sliding and compound motion modes. Wear. 530-531. 205062–205062. 7 indexed citations
9.
Peng, Yeping, et al.. (2023). Probability-weighted ensemble support vector machine for intelligent recognition of moving wear debris from joint implant. Tribology International. 186. 108583–108583. 7 indexed citations
10.
Peng, Yeping, et al.. (2022). Non-uniform illumination image enhancement for surface damage detection of wind turbine blades. Mechanical Systems and Signal Processing. 170. 108797–108797. 30 indexed citations
11.
Zhao, Genping, et al.. (2022). Phenotypic Parameters Estimation of Plants Using Deep Learning-Based 3-D Reconstruction From Single RGB Image. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 12 indexed citations
12.
Peng, Yeping, Mohammad Nazir Ahmad, Ali Abdollahi, et al.. (2021). Analysis of the effect of roughness and concentration of Fe3O4/water nanofluid on the boiling heat transfer using the artificial neural network: An experimental and numerical study. International Journal of Thermal Sciences. 163. 106863–106863. 48 indexed citations
14.
Wang, Baowei, et al.. (2019). Oxidative reforming of n-heptane in gliding arc plasma reformer for hydrogen production. International Journal of Hydrogen Energy. 44(41). 22831–22840. 17 indexed citations
15.
Li, Ruowei, Yeping Peng, Haiyan Shi, et al.. (2019). First-Order Difference Bare Bones Particle Swarm Optimizer. IEEE Access. 7. 132472–132491. 4 indexed citations
16.
Peng, Yeping, et al.. (2019). An Optimum Shift-and-Weighted brightness mapping for low-illumination image restoration. The Imaging Science Journal. 67(4). 187–201. 2 indexed citations
17.
Wu, Hongkun, Ruowei Li, N. M. Kwok, et al.. (2018). Restoration of low-informative image for robust debris shape measurement in on-line wear debris monitoring. Mechanical Systems and Signal Processing. 114. 539–555. 23 indexed citations
18.
Wu, Tonghai, et al.. (2014). Dimensional description of on-line wear debris images for wear characterization. Chinese Journal of Mechanical Engineering. 27(6). 1280–1286. 4 indexed citations
19.
Wu, Tonghai, et al.. (2014). Intelligent identification of wear mechanism via on-line ferrograph images. Chinese Journal of Mechanical Engineering. 27(2). 411–417. 13 indexed citations
20.
Wu, Hongkun, Tonghai Wu, Yeping Peng, & Zhongxiao Peng. (2013). Watershed-Based Morphological Separation of Wear Debris Chains for On-Line Ferrograph Analysis. Tribology Letters. 53(2). 411–420. 31 indexed citations

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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