Jingjun Gu
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
Papers in
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- Gear and Bearing Dynamics Analysis 6
- Mechanical Engineering and Vibrations Research 5
- Hydraulic and Pneumatic Systems 3
- Co-authors
- Jiajun Bu (10 shared papers)Sheng Zhou (4 shared papers)Xin Shen (1 shared paper)Zhe Liu (1 shared paper)Lei Wu (2 shared papers)Frédéric Sansoz (3 shared papers)Song Wang (2 shared papers)Jun Wen (2 shared papers)
- Journals
- Carbon (2 papers)Neural Networks (2 papers)IEEE Transactions on Medical Imaging (1 paper)Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (1 paper)Translational Psychiatry (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Jingjun Gu
20 papers receiving 295 citations
Peers
Comparison fields: 5 of 64
- Computer Vision and Pattern Recognition 115
- Health Informatics 5
- Neurology 23
- Radiology, Nuclear Medicine and Imaging 60
- Artificial Intelligence 96
Countries citing papers authored by Jingjun Gu
This map shows the geographic impact of Jingjun Gu'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 Jingjun Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingjun Gu more than expected).
Fields of papers citing papers by Jingjun Gu
This network shows the impact of papers produced by Jingjun Gu. 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 Jingjun Gu. The network helps show where Jingjun Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jingjun Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 141 | |
| 2 | 2020 | 21 | |
| 3 | 2022 | 20 | |
| 4 | 2022 | 17 | |
| 5 | 2013 | 16 | |
| 6 | 2024 | 12 | |
| 7 | 2019 | 11 | |
| 8 | 2016 | 11 | |
| 9 | 2021 | 10 | |
| 10 | 2018 | 7 | |
| 11 | 2013 | 7 | |
| 12 | 2021 | 6 | |
| 13 | 2015 | 6 | |
| 14 | 2024 | 4 | |
| 15 | 2019 | 3 | |
| 16 | 2017 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2024 | 1 | |
| 19 | Holospectrum analysis for bearing cage behaviour | 2015 | 1 |
| 20 | 2025 | 1 |
About Jingjun Gu
Jingjun Gu is a scholar working on Mechanical Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Control and Systems Engineering, having authored 24 papers that have together received 299 indexed citations. Recurring topics across this work include Gear and Bearing Dynamics Analysis (6 papers), Mechanical Engineering and Vibrations Research (5 papers), COVID-19 diagnosis using AI (3 papers), Advanced Neural Network Applications (3 papers), Hydraulic and Pneumatic Systems (3 papers), Carbon Nanotubes in Composites (3 papers), Metallurgy and Material Forming (2 papers) and Human Pose and Action Recognition (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (115 citations), Health Informatics (5 citations), Neurology (23 citations), Radiology, Nuclear Medicine and Imaging (60 citations) and Artificial Intelligence (96 citations). Jingjun Gu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Jiajun Bu, Sheng Zhou, Xin Shen, Zhe Liu, Lei Wu, Frédéric Sansoz, Song Wang, Jun Wen, Ning Ma and Ben Li. Their work appears in journals such as Carbon, Neural Networks, IEEE Transactions on Medical Imaging, Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology and Translational Psychiatry.
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.