Xiaojun Bi
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Cognitive Neuroscience top 10%
- Co-authors
- Chao WangChangdong YuYiwei FanJuan LyuSai Ho LingYang HanR.‐F. ShaoYiwen Sun
- Topics
- Cardiovascular Function and Risk Factors (16 papers)Metaheuristic Optimization Algorithms Research (13 papers)Advanced Neural Network Applications (12 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Xiaojun Bi
107 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 111
- Computer Vision and Pattern Recognition 327
- Artificial Intelligence 245
- Cardiology and Cardiovascular Medicine 166
- Radiology, Nuclear Medicine and Imaging 163
- Cognitive Neuroscience 162
Countries citing papers authored by Xiaojun Bi
This map shows the geographic impact of Xiaojun Bi'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 Xiaojun Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojun Bi more than expected).
Fields of papers citing papers by Xiaojun Bi
This network shows the impact of papers produced by Xiaojun Bi. 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 Xiaojun Bi. The network helps show where Xiaojun Bi may publish in the future.
Co-authorship network of co-authors of Xiaojun Bi
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojun Bi. A scholar is included among the top collaborators of Xiaojun Bi 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 Xiaojun Bi. Xiaojun Bi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 52 | |
| 8 | 2 | |
| 9 | 8 | |
| 10 | 1 | |
| 11 | 7 | |
| 12 | 13 | |
| 13 | 1 | |
| 14 | 20 | |
| 15 | 8 | |
| 16 | Studies on a longitudinal maneuvering motion control of underwater supercavitating vehicles | 0 |
| 17 | Advances in artificial immune systems | 1 |
| 18 | Improved Particle Swarm Optimization algorithm based on statistical laws and dynamic learning factors | 1 |
| 19 | Texture image recognizing method based on ant colony algorithm | 1 |
| 20 | Phenomenology of quintessino dark matter | 2 |
About Xiaojun Bi
Xiaojun Bi is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Cardiology and Cardiovascular Medicine, having authored 119 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (16 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Advanced Neural Network Applications (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (327 citations), Cognitive Neuroscience (162 citations) and Artificial Intelligence (245 citations). Xiaojun Bi has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Chao Wang, Changdong Yu, Yiwei Fan, Juan Lyu, Sai Ho Ling, Yang Han, R.‐F. Shao, Yiwen Sun, Chun‐Yu Chen and Jian Xiao. Their work appears in journals such as PLoS ONE, IEEE Transactions on Geoscience and Remote Sensing and Expert Systems with Applications.
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.