Baocai Yin
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Building and Construction top 10%
- Computational Mechanics
- Control and Systems Engineering
- Topics
- Human Pose and Action Recognition (14 papers)Advanced Vision and Imaging (13 papers)3D Shape Modeling and Analysis (12 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignHuman-Computer Interaction
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Baocai Yin
52 papers receiving 302 citations
Peers
Comparison fields: 5 of 68
- Computer Vision and Pattern Recognition 172
- Artificial Intelligence 64
- Building and Construction 61
- Computational Mechanics 42
- Control and Systems Engineering 39
Countries citing papers authored by Baocai Yin
This map shows the geographic impact of Baocai Yin'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 Baocai Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baocai Yin more than expected).
Fields of papers citing papers by Baocai Yin
This network shows the impact of papers produced by Baocai Yin. 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 Baocai Yin. The network helps show where Baocai Yin may publish in the future.
Co-authorship network of co-authors of Baocai Yin
This figure shows the co-authorship network connecting the top 25 collaborators of Baocai Yin. A scholar is included among the top collaborators of Baocai Yin 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 Baocai Yin. Baocai Yin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 8 | |
| 10 | 13 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 12 | |
| 14 | A Comprehensive Survey on Traffic Prediction. | 31 |
| 15 | 9 | |
| 16 | 8 | |
| 17 | 9 | |
| 18 | Lip Movement and Expression Database Construction for Chinese Sign Language Synthesis | 1 |
| 19 | The Diagnosis of Crop Pests and Diseases Based on the Heuristic Search | 1 |
| 20 | 1 |
About Baocai Yin
Baocai Yin is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mathematics, having authored 60 papers that have together received 316 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (14 papers), Advanced Vision and Imaging (13 papers) and 3D Shape Modeling and Analysis (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (172 citations), Computer Graphics and Computer-Aided Design (21 citations) and Human-Computer Interaction (31 citations). Baocai Yin has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Yong Zhang, Dehui Kong, Shaofan Wang, Bo Li, Jinghua Li, Xinglin Piao, Chengyang Zhang, Xiuping Liu, Weiming Wang and Xueyan Yin. Their work appears in journals such as Scientific Reports, Sensors and Pattern Recognition.
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.