Gaoqiang Kang

634 total citations · 1 hit paper
9 papers, 523 citations indexed

About

Gaoqiang Kang is a scholar working on Civil and Structural Engineering, Mechanical Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Gaoqiang Kang has authored 9 papers receiving a total of 523 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Civil and Structural Engineering, 5 papers in Mechanical Engineering and 5 papers in Industrial and Manufacturing Engineering. Recurrent topics in Gaoqiang Kang's work include Infrastructure Maintenance and Monitoring (5 papers), Railway Engineering and Dynamics (5 papers) and Electrical Contact Performance and Analysis (3 papers). Gaoqiang Kang is often cited by papers focused on Infrastructure Maintenance and Monitoring (5 papers), Railway Engineering and Dynamics (5 papers) and Electrical Contact Performance and Analysis (3 papers). Gaoqiang Kang collaborates with scholars based in China and United Kingdom. Gaoqiang Kang's co-authors include Dongkai Zhang, Long Yu, Shibin Gao, Shibin Gao, Xiaoguang Wei, Shengxian Zhuang, Jian Xiao, Jun Lin, Clive Roberts and Hu Wang and has published in prestigious journals such as IEEE Access, Solar Energy and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Gaoqiang Kang

9 papers receiving 517 citations

Hit Papers

Deep Architecture for Hig... 2018 2026 2020 2023 2018 50 100 150 200
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. Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning
    2018 219 citations Gaoqiang Kang, Shibin Gao 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
Gaoqiang Kang China 8 185 182 168 141 138 9 523
Rongfen Gong China 15 344 1.9× 113 0.6× 97 0.6× 74 0.5× 113 0.8× 29 527
Shuanlong Niu China 11 253 1.4× 114 0.6× 70 0.4× 58 0.4× 66 0.5× 15 392
Yincheng Qi China 9 106 0.6× 195 1.1× 104 0.6× 101 0.7× 29 0.2× 45 558
Fuqi Ma China 9 55 0.3× 88 0.5× 41 0.2× 136 1.0× 46 0.3× 33 383
Erhu Zhang China 10 261 1.4× 88 0.5× 112 0.7× 46 0.3× 74 0.5× 29 592
Yuekai Liu China 10 77 0.4× 157 0.9× 32 0.2× 186 1.3× 75 0.5× 16 550
Омкар Кулкарни India 7 56 0.3× 124 0.7× 30 0.2× 105 0.7× 114 0.8× 17 446
Tangbo Bai China 10 79 0.4× 173 1.0× 93 0.6× 62 0.4× 58 0.4× 22 437

Countries citing papers authored by Gaoqiang Kang

Since Specialization
Citations

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

Fields of papers citing papers by Gaoqiang Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gaoqiang Kang

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

All Works

9 of 9 papers shown
1.
Kang, Gaoqiang, et al.. (2023). Toward Reliable High-Speed Railway Pantograph-Catenary System State Detection: Multitask Deep Neural Networks With Runtime Reliability Monitoring. IEEE Transactions on Instrumentation and Measurement. 73. 1–11. 4 indexed citations
2.
Kang, Gaoqiang, et al.. (2021). Real-Time Defect Detection of Track Components: Considering Class Imbalance and Subtle Difference Between Classes. IEEE Transactions on Instrumentation and Measurement. 70. 1–12. 52 indexed citations
3.
Yu, Long, et al.. (2021). A Survey on Automatic Inspections of Overhead Contact Lines by Computer Vision. IEEE Transactions on Intelligent Transportation Systems. 23(8). 10104–10125. 24 indexed citations
4.
Zhang, Dongkai, et al.. (2020). DefGAN: Defect Detection GANs With Latent Space Pitting for High-Speed Railway Insulator. IEEE Transactions on Instrumentation and Measurement. 70. 1–10. 48 indexed citations
5.
Gao, Shibin, et al.. (2020). Adaptive Deep Learning for High-Speed Railway Catenary Swivel Clevis Defects Detection. IEEE Transactions on Intelligent Transportation Systems. 23(2). 1299–1310. 22 indexed citations
6.
Kang, Gaoqiang, et al.. (2019). Contact Wire Support Defect Detection Using Deep Bayesian Segmentation Neural Networks and Prior Geometric Knowledge. IEEE Access. 7. 173366–173376. 17 indexed citations
7.
Zhang, Dongkai, et al.. (2019). A Robust Pantograph–Catenary Interaction Condition Monitoring Method Based on Deep Convolutional Network. IEEE Transactions on Instrumentation and Measurement. 69(5). 1920–1929. 41 indexed citations
8.
Kang, Gaoqiang, Shibin Gao, Long Yu, & Dongkai Zhang. (2018). Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning. IEEE Transactions on Instrumentation and Measurement. 68(8). 2679–2690. 219 indexed citations breakdown →
9.
Zhuang, Shengxian, et al.. (2017). An ensemble prediction intervals approach for short-term PV power forecasting. Solar Energy. 155. 1072–1083. 96 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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