Shaoyu Chen
- Computer Vision and Pattern Recognition top 5%
- Automotive Engineering top 10%
- Artificial Intelligence
- Aerospace Engineering
- Human-Computer Interaction top 10%
- Co-authors
- Xinggang WangWenyu LiuQian ZhangChang HuangTianheng ChengWenqiang ZhangZhaoxiang ZhangBencheng Liao
- Topics
- Advanced Neural Network Applications (6 papers)Advanced Image and Video Retrieval Techniques (4 papers)Augmented Reality Applications (3 papers)
- Journals
- International Journal of Computer VisionApplied GeochemistryIEEE Transactions on Visualization and Computer Graphics
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Shaoyu Chen
24 papers receiving 378 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 215
- Automotive Engineering 77
- Artificial Intelligence 71
- Aerospace Engineering 51
- Human-Computer Interaction 36
Countries citing papers authored by Shaoyu Chen
This map shows the geographic impact of Shaoyu Chen'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 Shaoyu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoyu Chen more than expected).
Fields of papers citing papers by Shaoyu Chen
This network shows the impact of papers produced by Shaoyu Chen. 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 Shaoyu Chen. The network helps show where Shaoyu Chen may publish in the future.
Co-authorship network of co-authors of Shaoyu Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Shaoyu Chen. A scholar is included among the top collaborators of Shaoyu Chen 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 Shaoyu Chen. Shaoyu Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 42 | |
| 9 | 12 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 1 | |
| 13 | 77 | |
| 14 | 9 | |
| 15 | 114 | |
| 16 | 20 | |
| 17 | 1 | |
| 18 | 5 | |
| 19 | 2 | |
| 20 | 14 |
About Shaoyu Chen
Shaoyu Chen is a scholar working on Human Factors and Ergonomics, Computer Vision and Pattern Recognition and Automotive Engineering, having authored 29 papers that have together received 390 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Augmented Reality Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (215 citations), Human-Computer Interaction (36 citations) and Automotive Engineering (77 citations). Shaoyu Chen has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Xinggang Wang, Wenyu Liu, Qian Zhang, Chang Huang, Tianheng Cheng, Wenqiang Zhang, Zhaoxiang Zhang, Bencheng Liao, Helong Zhou and Jiajie Chen. Their work appears in journals such as International Journal of Computer Vision, Applied Geochemistry and IEEE Transactions on Visualization and Computer Graphics.
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.