Yanjun Peng
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Context-Aware Activity Recognition Systems
- Neurology top 5%
- Brain Tumor Detection and Classification
Papers in
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- Advanced Neural Network Applications 23
- Medical Image Segmentation Techniques 17
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- Radiomics and Machine Learning in Medical Imaging 23
- COVID-19 diagnosis using AI 9
- Co-authors
- Yanfei Guo (22 shared papers)Peter W. Tse (1 shared paper)Richard C.M. Yam (1 shared paper)Lingmei Ren (2 shared papers)Dapeng Li (4 shared papers)Shu‐Chuan Chu (2 shared papers)Jeng‐Shyang Pan (2 shared papers)Xinming Lu (7 shared papers)
- Journals
- Biomedical Signal Processing and Control (6 papers)Multimedia Tools and Applications (6 papers)Knowledge-Based Systems (4 papers)Applied Intelligence (3 papers)IEEE Access (3 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Yanjun Peng
102 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 142
- Computer Vision and Pattern Recognition 571
- Neurology 199
- Control and Systems Engineering 350
- Radiology, Nuclear Medicine and Imaging 283
- Artificial Intelligence 371
Countries citing papers authored by Yanjun Peng
This map shows the geographic impact of Yanjun Peng'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 Yanjun Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanjun Peng more than expected).
Fields of papers citing papers by Yanjun Peng
This network shows the impact of papers produced by Yanjun Peng. 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 Yanjun Peng. The network helps show where Yanjun Peng may publish in the future.
Co-authors
The 25 scholars most cited alongside Yanjun Peng, 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 114 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 348 | |
| 2 | 2019 | 194 | |
| 3 | 2020 | 147 | |
| 4 | 2017 | 106 | |
| 5 | 2020 | 72 | |
| 6 | 2018 | 69 | |
| 7 | 2022 | 52 | |
| 8 | 2013 | 48 | |
| 9 | 2021 | 46 | |
| 10 | 2017 | 43 | |
| 11 | 2018 | 38 | |
| 12 | 2010 | 37 | |
| 13 | 2021 | 35 | |
| 14 | 2022 | 34 | |
| 15 | 2018 | 32 | |
| 16 | 2018 | 31 | |
| 17 | 2020 | 30 | |
| 18 | 2018 | 29 | |
| 19 | 2021 | 27 | |
| 20 | 2022 | 24 |
About Yanjun Peng
Yanjun Peng is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computational Mechanics and Biomedical Engineering, having authored 114 papers that have together received 1.9k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (23 papers), Radiomics and Machine Learning in Medical Imaging (23 papers), AI in cancer detection (18 papers), Medical Image Segmentation Techniques (17 papers), Brain Tumor Detection and Classification (13 papers), 3D Shape Modeling and Analysis (11 papers), COVID-19 diagnosis using AI (9 papers) and Gear and Bearing Dynamics Analysis (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (571 citations), Neurology (199 citations), Control and Systems Engineering (350 citations), Radiology, Nuclear Medicine and Imaging (283 citations) and Artificial Intelligence (371 citations). Yanjun Peng has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yanfei Guo, Peter W. Tse, Richard C.M. Yam, Lingmei Ren, Dapeng Li, Shu‐Chuan Chu, Jeng‐Shyang Pan, Xinming Lu, Ning Zhao and Pei-Cheng Song. Their work appears in journals such as Biomedical Signal Processing and Control, Multimedia Tools and Applications, Knowledge-Based Systems, Applied Intelligence and IEEE Access.
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.