Yonghong Peng
Impact in
- Artificial Intelligence top 2%
- AI in cancer detection
- Text and Document Classification Technologies
Papers in
-
- Human Pose and Action Recognition 13
- Video Surveillance and Tracking Methods 9
- Face recognition and analysis 7
- Multimodal Machine Learning Applications 5
-
- Anomaly Detection Techniques and Applications 8
- Co-authors
- Peter CowlingFadi ThabtahJianmin JiangZhiqing WuLinbo QingYongqiang ChengXuezhong ZhouBaoyan Liu
- Journals
- IEEE Access (17 papers)Neural Computing and Applications (4 papers)Neurocomputing (4 papers)Diabetes Therapy (4 papers)The Visual Computer (3 papers)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Yonghong Peng
118 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 178
- Artificial Intelligence 753
- Computer Vision and Pattern Recognition 464
- Health Information Management 88
- Information Systems 315
- Complementary and alternative medicine 111
Countries citing papers authored by Yonghong Peng
This map shows the geographic impact of Yonghong 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 Yonghong Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yonghong Peng more than expected).
Fields of papers citing papers by Yonghong Peng
This network shows the impact of papers produced by Yonghong 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 Yonghong Peng. The network helps show where Yonghong Peng may publish in the future.
Co-authors
The 25 scholars most cited alongside Yonghong 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 7 | |
| 7 | 2023 | 12 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 1 | |
| 10 | 2022 | 10 | |
| 11 | 2021 | 2 | |
| 12 | 2021 | 2 | |
| 13 | 2020 | 102 | |
| 14 | 2020 | 29 | |
| 15 | 2019 | 97 | |
| 16 | 2010 | 100 | |
| 17 | 2009 | 25 | |
| 18 | 2009 | 184 | |
| 19 | 2005 | 9 | |
| 20 | Improved data set characterisation for meta-learning | 2002 | 9 |
About Yonghong Peng
Yonghong Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Computer Graphics and Computer-Aided Design and Complementary and alternative medicine, having authored 126 papers that have together received 2.5k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (13 papers), Video Surveillance and Tracking Methods (9 papers), Gene expression and cancer classification (8 papers), Anomaly Detection Techniques and Applications (8 papers), Face recognition and analysis (7 papers), Multimodal Machine Learning Applications (5 papers), Biomedical Text Mining and Ontologies (5 papers) and Data Mining Algorithms and Applications (5 papers). The work is most often cited by research in Artificial Intelligence (753 citations), Computer Vision and Pattern Recognition (464 citations), Health Information Management (88 citations), Information Systems (315 citations) and Complementary and alternative medicine (111 citations). Yonghong Peng has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Peter Cowling, Fadi Thabtah, Jianmin Jiang, Zhiqing Wu, Linbo Qing, Yongqiang Cheng, Xuezhong Zhou, Baoyan Liu, Nianyin Zeng and Chenxi Huang. Their work appears in journals such as IEEE Access, Neural Computing and Applications, Neurocomputing, Diabetes Therapy and The Visual Computer.
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.