Jiangtao Wen

1.6k total citations · 1 hit paper
35 papers, 1.3k citations indexed

About

Jiangtao Wen is a scholar working on Civil and Structural Engineering, Control and Systems Engineering and Mechanics of Materials. According to data from OpenAlex, Jiangtao Wen has authored 35 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Civil and Structural Engineering, 9 papers in Control and Systems Engineering and 9 papers in Mechanics of Materials. Recurrent topics in Jiangtao Wen's work include Machine Fault Diagnosis Techniques (7 papers), Water Systems and Optimization (5 papers) and Video Coding and Compression Technologies (4 papers). Jiangtao Wen is often cited by papers focused on Machine Fault Diagnosis Techniques (7 papers), Water Systems and Optimization (5 papers) and Video Coding and Compression Technologies (4 papers). Jiangtao Wen collaborates with scholars based in China, United States and Australia. Jiangtao Wen's co-authors include Jiedi Sun, Changhong Yan, Qiyang Xiao, Weixin Li, Guan Wang, Wei Meng, Dong Xuan, Yi Pang, Fei Wang and Yao Lu and has published in prestigious journals such as IEEE Access, Sensors and Pattern Recognition.

In The Last Decade

Jiangtao Wen

30 papers receiving 1.2k citations

Hit Papers

Intelligent Bearing Fault Diagnosis Method Combining Comp... 2017 2026 2020 2023 2017 100 200 300
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.

  1. Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning
    2017 344 citations Jiedi Sun, Changhong Yan et al. IEEE Transactions on Instrumentation and Measurement profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiangtao Wen China 16 501 410 343 264 223 35 1.3k
Gang Tang China 24 877 1.8× 572 1.4× 169 0.5× 133 0.5× 310 1.4× 72 1.4k
Jiedi Sun China 14 527 1.1× 458 1.1× 61 0.2× 330 1.3× 232 1.0× 21 1.0k
Gang Yu China 17 1.3k 2.6× 586 1.4× 285 0.8× 546 2.1× 382 1.7× 54 1.7k
Yifan Li China 24 997 2.0× 906 2.2× 82 0.2× 258 1.0× 355 1.6× 101 1.6k
Liangsheng Qu China 18 1.0k 2.1× 629 1.5× 151 0.4× 265 1.0× 298 1.3× 36 1.5k
Gaigai Cai China 14 1.1k 2.3× 798 1.9× 129 0.4× 396 1.5× 318 1.4× 32 1.5k
Cristinel Mares United Kingdom 17 147 0.3× 379 0.9× 191 0.6× 762 2.9× 286 1.3× 63 1.1k
Wenhua Du China 19 1.2k 2.4× 851 2.1× 107 0.3× 202 0.8× 369 1.7× 44 1.6k

Countries citing papers authored by Jiangtao Wen

Since Specialization
Citations

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

Fields of papers citing papers by Jiangtao Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiangtao Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Jiangtao Wen. A scholar is included among the top collaborators of Jiangtao Wen 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 Jiangtao Wen. Jiangtao Wen 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.
Li, Jian, Lijie Dong, Jiangtao Wen, et al.. (2025). A Case Study of Operating Strategy Analysis of Heating and Cooling Source Units for a Large Sports Center. Buildings. 15(23). 4301–4301.
2.
Li, Xiaoxin, et al.. (2025). A lightweight model based on knowledge distillation for free-range chickens detection in complex commercial farming environments. Artificial Intelligence in Agriculture. 16(1). 266–283.
3.
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5.
Lei, Yiming, et al.. (2024). An efficient Kriging-based calibration framework for FDEM. Engineering Fracture Mechanics. 296. 109857–109857. 17 indexed citations
6.
Lin, Peng, Chongshan Yang, Jun Zhang, et al.. (2024). Rapid and accurate detection of total nitrogen in the different types for soil using laser-induced breakdown spectroscopy combined with transfer learning. Computers and Electronics in Agriculture. 226. 109396–109396. 2 indexed citations
7.
Li, Xiaoxin, et al.. (2024). An efficient transformer network for detecting multi-scale chicken in complex free-range farming environments via improved RT-DETR. Computers and Electronics in Agriculture. 224. 109160–109160. 26 indexed citations
8.
Wang, Zhao, et al.. (2023). DarkFeat: Noise-Robust Feature Detector and Descriptor for Extremely Low-Light RAW Images. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 826–834. 6 indexed citations
9.
Li, Yanghao, et al.. (2023). Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos. 22627–22637. 5 indexed citations
10.
Sun, Jiedi, et al.. (2022). Multiple hierarchical compression for deep neural network toward intelligent bearing fault diagnosis. Engineering Applications of Artificial Intelligence. 116. 105498–105498. 35 indexed citations
11.
Sun, Jiedi, et al.. (2021). Bearing Fault Diagnosis Based on Multiple Transformation Domain Fusion and Improved Residual Dense Networks. IEEE Sensors Journal. 22(2). 1541–1551. 43 indexed citations
12.
Sun, Jiedi, Zhitao Peng, & Jiangtao Wen. (2017). Leakage aperture recognition based on ensemble local mean decomposition and sparse representation for classification of natural gas pipeline. Measurement. 108. 91–100. 22 indexed citations
13.
Sun, Jiedi, Changhong Yan, & Jiangtao Wen. (2017). Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning. IEEE Transactions on Instrumentation and Measurement. 67(1). 185–195. 344 indexed citations breakdown →
14.
Sun, Jiedi, Qiyang Xiao, Jiangtao Wen, & Ying Zhang. (2015). Natural gas pipeline leak aperture identification and location based on local mean decomposition analysis. Measurement. 79. 147–157. 99 indexed citations
15.
Liu, Weibo, et al.. (2015). Research on surface seismic source location method based on local mean decomposition and time difference of arrival. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9794. 979418–979418. 1 indexed citations
16.
Sun, Jiedi, Qiyang Xiao, Jiangtao Wen, & Fei Wang. (2014). Natural gas pipeline small leakage feature extraction and recognition based on LMD envelope spectrum entropy and SVM. Measurement. 55. 434–443. 153 indexed citations
17.
Villasenor, John, et al.. (2012). THE INFORMATION RATE OF MODERN SPEECH AND ITS IMPLICATIONS FOR LANGUAGE EVOLUTION. The Evolution of Language. 376–383. 1 indexed citations
18.
Xuan, Dong, Guan Wang, Yi Pang, et al.. (2011). Fast efficient algorithm for enhancement of low lighting video. 1–6. 264 indexed citations
19.
20.
Wen, Jiangtao. (2002). The Study of Processing to Outlier in Measured Data Based on Robust Filtering. 1 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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