Yanping Bai
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
- Toxicology top 5%
Papers in
-
- Advanced Algorithms and Applications 16
- Advanced Sensor and Control Systems 9
-
- Neural Networks and Applications 7
- AI in cancer detection 6
- Co-authors
- Hongping Hu (33 shared papers)Zhen Jin (3 shared papers)Rong Cheng (10 shared papers)Shuicai Wu (17 shared papers)Peng Wang (9 shared papers)Wendong Zhang (9 shared papers)Linmei Zhang (4 shared papers)Ting Xu (1 shared paper)
- Journals
- IEEE Access (6 papers)Sensors (5 papers)PLoS ONE (4 papers)Chaos Solitons & Fractals (3 papers)Computational Intelligence and Neuroscience (2 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Yanping Bai
81 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 144
- Modeling and Simulation 124
- Toxicology 42
- Artificial Intelligence 401
- Radiology, Nuclear Medicine and Imaging 180
- Computer Vision and Pattern Recognition 166
Countries citing papers authored by Yanping Bai
This map shows the geographic impact of Yanping Bai'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 Yanping Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanping Bai more than expected).
Fields of papers citing papers by Yanping Bai
This network shows the impact of papers produced by Yanping Bai. 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 Yanping Bai. The network helps show where Yanping Bai may publish in the future.
Co-authors
The 25 scholars most cited alongside Yanping Bai, 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 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 111 | |
| 2 | 2014 | 68 | |
| 3 | 2019 | 59 | |
| 4 | 2005 | 57 | |
| 5 | 2016 | 49 | |
| 6 | 2014 | 42 | |
| 7 | 2019 | 41 | |
| 8 | 2019 | 40 | |
| 9 | 2022 | 39 | |
| 10 | 2019 | 39 | |
| 11 | 2005 | 38 | |
| 12 | 2020 | 36 | |
| 13 | 2021 | 34 | |
| 14 | 2020 | 34 | |
| 15 | 2019 | 30 | |
| 16 | 2016 | 29 | |
| 17 | 2021 | 28 | |
| 18 | 2018 | 28 | |
| 19 | 2015 | 25 | |
| 20 | 2014 | 24 |
About Yanping Bai
Yanping Bai is a scholar working on Control and Systems Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Radiology, Nuclear Medicine and Imaging, having authored 87 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Algorithms and Applications (16 papers), Advanced Sensor and Control Systems (9 papers), Neural Networks and Applications (7 papers), Vehicle License Plate Recognition (6 papers), Underwater Acoustics Research (6 papers), AI in cancer detection (6 papers), Ultrasound and Hyperthermia Applications (6 papers) and Digital Imaging for Blood Diseases (5 papers). The work is most often cited by research in Modeling and Simulation (124 citations), Toxicology (42 citations), Artificial Intelligence (401 citations), Radiology, Nuclear Medicine and Imaging (180 citations) and Computer Vision and Pattern Recognition (166 citations). Yanping Bai has collaborated with scholars based in China and United States. Frequent co-authors include Hongping Hu, Zhen Jin, Rong Cheng, Shuicai Wu, Peng Wang, Wendong Zhang, Linmei Zhang, Ting Xu, Peng Wang and Ting Xu. Their work appears in journals such as IEEE Access, Sensors, PLoS ONE, Chaos Solitons & Fractals and Computational Intelligence and Neuroscience.
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.