Jingke Yan

441 total citations · 2 hit papers
19 papers, 227 citations indexed

About

Jingke Yan is a scholar working on Mechanical Engineering, Computer Vision and Pattern Recognition and Civil and Structural Engineering. According to data from OpenAlex, Jingke Yan has authored 19 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Mechanical Engineering, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Civil and Structural Engineering. Recurrent topics in Jingke Yan's work include Electrical Contact Performance and Analysis (4 papers), Infrastructure Maintenance and Monitoring (4 papers) and Railway Systems and Energy Efficiency (3 papers). Jingke Yan is often cited by papers focused on Electrical Contact Performance and Analysis (4 papers), Infrastructure Maintenance and Monitoring (4 papers) and Railway Systems and Energy Efficiency (3 papers). Jingke Yan collaborates with scholars based in China, Portugal and Hong Kong. Jingke Yan's co-authors include Bo Jin, Weihua Zhang, Yao Cheng, Ning Zhou, Cheng Yao, Qin Qin, Fan Zhang, Chuanxin Shi, Hui Wang and Fan Zhang and has published in prestigious journals such as Scientific Reports, IEEE Access and IEEE Transactions on Vehicular Technology.

In The Last Decade

Jingke Yan

13 papers receiving 220 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.

Transformer and Graph Convolution-Based Unsupervised Detection of Machine Anomalous Sound Under Domain Shifts

2024 59 citations Jingke Yan, Yao Cheng et al. IEEE Transactions on Emerging Topics in Computational Intelligence profile →
Multimodal Imitation Learning for Arc Detection in Complex Railway Environments

2025 27 citations Jingke Yan, Yao Cheng et al. IEEE Transactions on Instrumentation and Measurement profile →

Peers

Jingke Yan

CSE

CVPR

IME

Kang Yang China

Yun Teng China

Mingkai Zheng China

Yongzhi Min China

Boxiong Yang China

Stephen Vidas Australia

Xinyu Yang China

Qingfeng Xia China

Xiaoyu Chen China

Kang Yang China

Jingke Yan

45 ×0.6

CSE

34 ×0.5

126 ×2.2

CVPR

47 ×1.5

10 ×0.4

IME

Citations per year, relative to Jingke Yan Jingke Yan (= 1×) peers Kang Yang

Countries citing papers authored by Jingke Yan

Since Specialization

Citations

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

Fields of papers citing papers by Jingke Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingke Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Jingke Yan. A scholar is included among the top collaborators of Jingke Yan 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 Jingke Yan. Jingke Yan 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:

19 of 19 papers shown

Wang, Hui, et al.. (2025). Physics-Informed Enhanced Fourier Neural Operator for Solving Pantograph-Catenary Interaction in Electric Railway. IEEE Transactions on Vehicular Technology. 75(1). 482–493.

Yan, Jingke, Yao Cheng, Fan Zhang, et al.. (2025). Multimodal Imitation Learning for Arc Detection in Complex Railway Environments. IEEE Transactions on Instrumentation and Measurement. 74. 1–13. 27 indexed citations breakdown →

Zhang, Fan, et al.. (2025). A novel edge intelligence application model with lightweight network and antinoise ability for bearing fault diagnosis. Structural Health Monitoring.

Wang, Yixuan & Jingke Yan. (2025). Research on Camouflaged Object Segmentation Based on Feature Fusion and Attention Mechanism. IET Image Processing. 19(1).

Zhang, Fan, Zhaoqi Li, Cheng Yao, et al.. (2025). MHSNet: A Multi-Scale Hidden State Interaction Network for Fault Diagnosis of Rotating Machinery. Tsinghua Science & Technology.

Yan, Jingke, Cheng Yao, Fan Zhang, et al.. (2025). Research on multimodal techniques for arc detection in railway systems with limited data. Structural Health Monitoring. 13 indexed citations

Zhou, Ning, et al.. (2025). A semi-supervised learning framework for bearing fault recognition under strong noise. Structural Health Monitoring.

Wang, Xin, et al.. (2024). Semantic segmentation network for mangrove tree species based on UAV remote sensing images. Scientific Reports. 14(1). 29860–29860. 5 indexed citations

Yao, Cheng, Jingke Yan, Fan Zhang, et al.. (2024). Surrogate modeling of pantograph-catenary system interactions. Mechanical Systems and Signal Processing. 224. 112134–112134. 48 indexed citations

10.

Yan, Jingke, et al.. (2024). A Crowd Counting and Localization Network Based on Adaptive Feature Fusion and Multi-Scale Global Attention Up Sampling. IEEE Access. 12. 12919–12939. 1 indexed citations

11.

Yan, Jingke, et al.. (2024). Transformer and Graph Convolution-Based Unsupervised Detection of Machine Anomalous Sound Under Domain Shifts. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(4). 2827–2842. 59 indexed citations breakdown →

12.

Zhou, Ning, et al.. (2024). Study on thermo-mechanical coupling model in pantograph-catenary system of rail vehicle. Journal of Physics Conference Series. 2808(1). 12079–12079.

13.

Huang, Li, et al.. (2024). Improving image super-resolution with structured knowledge distillation-based multimodal denoising diffusion probabilistic model. Journal of Electronic Imaging. 33(3). 3 indexed citations

14.

Yan, Jingke, et al.. (2024). Optimized single-image super-resolution reconstruction: A multimodal approach based on reversible guidance and cyclical knowledge distillation. Engineering Applications of Artificial Intelligence. 133. 108496–108496. 10 indexed citations

15.

Yan, Jingke, Zhe Zheng, Yucheng Zhou, et al.. (2023). Recent Research Progress in Intelligent Construction: A Comparison between China and Developed Countries. Buildings. 13(5). 1329–1329. 14 indexed citations

16.

Yan, Jingke, et al.. (2022). Earf-YOLO: An Efficient Attention Receptive Field Model for Recognizing Symbols of Zhuang Minority Patterns. Mathematical Problems in Engineering. 2022. 1–14. 2 indexed citations

17.

Yan, Jingke, Xin Wang, Jingye Cai, et al.. (2022). Medical image segmentation model based on triple gate MultiLayer perceptron. Scientific Reports. 12(1). 6103–6103. 23 indexed citations

18.

Yan, Jingke, Zhe Zheng, Yucheng Zhou, Jia‐Rui Lin, & Yichuan Deng. (2022). A Review on Current Advances of Intelligent Construction Based on Bibliometric Analysis. 340–355. 1 indexed citations

19.

Qin, Qin, et al.. (2021). ETDNet: An Efficient Transformer Deraining Model. IEEE Access. 9. 119881–119893. 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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