Yue Bai
- Human-Computer Interaction top 2%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Developmental and Educational Psychology top 10%
- Artificial Intelligence
- Co-authors
- Yun FuLichen WangSongyao JiangKunpeng LiCan QinHuan WangYulun ZhangSheng Li
- Topics
- Anomaly Detection Techniques and Applications (5 papers)Human Pose and Action Recognition (3 papers)Network Security and Intrusion Detection (3 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionDevelopmental and Educational Psychology
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Knowledge and Data EngineeringEuropean Neuropsychopharmacology
- Partner nations
- United StatesMexicoSwitzerland
In The Last Decade
Yue Bai
14 papers receiving 249 citations
Peers
Comparison fields: 5 of 46
- Human-Computer Interaction 149
- Computer Vision and Pattern Recognition 136
- Biomedical Engineering 91
- Developmental and Educational Psychology 75
- Artificial Intelligence 55
Countries citing papers authored by Yue Bai
This map shows the geographic impact of Yue 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 Yue Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yue Bai more than expected).
Fields of papers citing papers by Yue Bai
This network shows the impact of papers produced by Yue 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 Yue Bai. The network helps show where Yue Bai may publish in the future.
Co-authorship network of co-authors of Yue Bai
This figure shows the co-authorship network connecting the top 25 collaborators of Yue Bai. A scholar is included among the top collaborators of Yue Bai 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 Yue Bai. Yue Bai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 15 | |
| 6 | 27 | |
| 7 | 4 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 159 | |
| 11 | 15 | |
| 12 | 3 | |
| 13 | 19 | |
| 14 | 1 |
About Yue Bai
Yue Bai is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 14 papers that have together received 258 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (5 papers), Human Pose and Action Recognition (3 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Human-Computer Interaction (149 citations), Computer Vision and Pattern Recognition (136 citations) and Developmental and Educational Psychology (75 citations). Yue Bai has collaborated with scholars based in United States, Mexico and Switzerland. Frequent co-authors include Yun Fu, Lichen Wang, Songyao Jiang, Kunpeng Li, Can Qin, Yun Fu, Huan Wang, Yulun Zhang, Sheng Li and Yi Xu. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Knowledge and Data Engineering and European Neuropsychopharmacology.
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.