Yehu Shen

1.4k total citations · 1 hit paper
62 papers, 926 citations indexed

About

Yehu Shen is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Yehu Shen has authored 62 papers receiving a total of 926 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Control and Systems Engineering, 27 papers in Computer Vision and Pattern Recognition and 20 papers in Mechanical Engineering. Recurrent topics in Yehu Shen's work include Machine Fault Diagnosis Techniques (22 papers), Engineering Diagnostics and Reliability (11 papers) and Gear and Bearing Dynamics Analysis (10 papers). Yehu Shen is often cited by papers focused on Machine Fault Diagnosis Techniques (22 papers), Engineering Diagnostics and Reliability (11 papers) and Gear and Bearing Dynamics Analysis (10 papers). Yehu Shen collaborates with scholars based in China, United Kingdom and United States. Yehu Shen's co-authors include Quan Jiang, Qixin Zhu, Fengyu Xu, Qingkui Zhang, Chenhui Qian, Qicong Wang, Jilin Liu, Xiaoshan Lin, Ümi̇t Özgüner and Keith Redmill and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Sensors.

In The Last Decade

Yehu Shen

57 papers receiving 893 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Application of recurrent neural network to mechanical fault diagnosis: a review

2022 110 citations Quan Jiang, Yehu Shen et al. profile →

Peers

Yehu Shen

CSE

ME

CVPR

MM

AI

Xiong Hu China

Clemens Gühmann Germany

Cheol Hong Kim South Korea

Yan Han China

Hao Sun China

Chao Tan China

Huimin Zhao China

Jin Huang China

Shulin Liu China

H. Tran-Ngoc Vietnam

Xiong Hu China

Yehu Shen

451 ×0.9

CSE

217 ×0.7

ME

218 ×1.1

CVPR

116 ×0.7

MM

81 ×0.6

AI

Citations per year, relative to Yehu Shen Yehu Shen (= 1×) peers Xiong Hu

Countries citing papers authored by Yehu Shen

Since Specialization

Citations

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

Fields of papers citing papers by Yehu Shen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yehu Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Yehu Shen. A scholar is included among the top collaborators of Yehu Shen 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 Yehu Shen. Yehu Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Shen, Yehu, Jiahao Du, Yifan He, et al.. (2025). AAKAN-WGAN: Predicting mechanical properties of magnesium alloys based on generative design and adaptive activation of Kolmogorov-Arnold Networks. Materials Today Communications. 47. 113198–113198. 1 indexed citations

2.

Chen, Huaixin, et al.. (2025). EVSPSA: an elongated variable stiffness pneumatic soft actuator for rigid-soft coupling gripper. Smart Materials and Structures. 34(9). 95034–95034.

3.

Fu, Guizhong, et al.. (2025). A fast steel surface defect inspection approach using contextual anchor attention and bidirectional feature pyramid fusion network. Measurement Science and Technology. 36(5). 55002–55002. 1 indexed citations

4.

Jiang, Quan, et al.. (2024). SSPENet: Semi-supervised prototype enhancement network for rolling bearing fault diagnosis under limited labeled samples. Advanced Engineering Informatics. 61. 102560–102560. 19 indexed citations

5.

Jiang, Quan, et al.. (2024). Remaining useful life prediction model of cross-domain rolling bearing via dynamic hybrid domain adaptation and attention contrastive learning. Computers in Industry. 164. 104172–104172. 13 indexed citations

6.

Shen, Yehu, et al.. (2024). Touchless Finger Vein and Fingerprint Verification via Exploiting Attention-Based Cross-Domain Fusion. IEEE Transactions on Circuits and Systems for Video Technology. 35(4). 3426–3437.

7.

Shen, Yehu, et al.. (2024). OLM-SLAM: online lifelong memory system for simultaneous localization and mapping. Measurement Science and Technology. 36(1). 16328–16328. 1 indexed citations

8.

Fu, Guizhong, Jiaao Chen, Si-Jin Qian, et al.. (2024). An weak surface defect inspection approach using efficient multi-scale attention and space-to-depth convolution network. Measurement. 243. 116220–116220. 1 indexed citations

9.

Zhang, Daqing, Yehu Shen, Jinbin Lu, et al.. (2024). IPR-VINS: Real-time monocular visual-inertial SLAM with implicit plane optimization. Measurement. 226. 114099–114099. 6 indexed citations

10.

Jiang, Quan, et al.. (2023). Res-HSA: Residual hybrid network with self-attention mechanism for RUL prediction of rotating machinery. Engineering Applications of Artificial Intelligence. 124. 106491–106491. 33 indexed citations

11.

Jiang, Quan, et al.. (2023). A class-level matching unsupervised transfer learning network for rolling bearing fault diagnosis under various working conditions. Applied Soft Computing. 146. 110739–110739. 27 indexed citations

12.

Lin, Xiaoshan, Quan Jiang, Yehu Shen, Fengyu Xu, & Qingkui Zhang. (2023). Multiscale Pooled Convolutional Domain Adaptation Network for Intelligent Diagnosis of Rolling Bearing Under Variable Conditions. IEEE Sensors Journal. 23(21). 26163–26176. 4 indexed citations

13.

Jiang, Quan, et al.. (2023). RUL prediction method for rolling bearing using convolutional denoising autoencoder and bidirectional LSTM. Measurement Science and Technology. 35(3). 35111–35111. 26 indexed citations

14.

Wang, Qicong, et al.. (2023). SSRL: Self-Supervised Spatial-Temporal Representation Learning for 3D Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology. 34(1). 274–285. 9 indexed citations

15.

Jiang, Quan, et al.. (2023). An unsupervised transfer learning approach for rolling bearing fault diagnosis based on dual pseudo-label screening. Structural Health Monitoring. 23(4). 2288–2309. 5 indexed citations

16.

Jiang, Quan, et al.. (2023). New RUL Prediction Method for Rotating Machinery via Data Feature Distribution and Spatial Attention Residual Network. IEEE Transactions on Instrumentation and Measurement. 72. 1–9. 20 indexed citations

17.

Fu, Guizhong, et al.. (2023). A Surface Defect Inspection Model via Rich Feature Extraction and Residual-Based Progressive Integration CNN. Machines. 11(1). 124–124. 7 indexed citations

18.

Li, Xing, et al.. (2022). DyStSLAM: an efficient stereo vision SLAM system in dynamic environment. Measurement Science and Technology. 34(2). 25105–25105. 10 indexed citations

19.

Dai, Yifan, et al.. (2021). Robust Vehicle Dynamics Control for a Sharp Curve With Uncertain Road Condition. Frontiers in Energy Research. 9. 1 indexed citations

20.

Zhao, Chong, et al.. (2019). 3D Behavior Recognition Based on Multi-Modal Deep Space-Time Learning. Applied Sciences. 9(4). 716–716. 21 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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