Bing Bai
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Aerospace Engineering
- Safety, Risk, Reliability and Quality top 10%
- Automotive Engineering
- Co-authors
- Bineng ZhongYun FuYulun ZhangJun LiYogesh BalajiHans Peter GrafRama ChellappaMartin Renqiang Min
- Topics
- Video Surveillance and Tracking Methods (5 papers)Advanced Image and Video Retrieval Techniques (4 papers)Autonomous Vehicle Technology and Safety (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionSafety, Risk, Reliability and QualityArtificial Intelligence
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Bing Bai
16 papers receiving 258 citations
Peers
Comparison fields: 5 of 50
- Computer Vision and Pattern Recognition 210
- Artificial Intelligence 77
- Aerospace Engineering 32
- Safety, Risk, Reliability and Quality 28
- Automotive Engineering 21
Countries citing papers authored by Bing Bai
This map shows the geographic impact of Bing 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 Bing Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing Bai more than expected).
Fields of papers citing papers by Bing Bai
This network shows the impact of papers produced by Bing 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 Bing Bai. The network helps show where Bing Bai may publish in the future.
Co-authorship network of co-authors of Bing Bai
This figure shows the co-authorship network connecting the top 25 collaborators of Bing Bai. A scholar is included among the top collaborators of Bing 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 Bing Bai. Bing 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 | 3 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 14 | |
| 8 | Spatio-temporal Consistency and Hierarchical Matching for Multi-Target Multi-Camera Vehicle Tracking | 19 |
| 9 | 3 | |
| 10 | 62 | |
| 11 | 63 | |
| 12 | 26 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 60 | |
| 17 | 1 | |
| 18 | 4 |
About Bing Bai
Bing Bai is a scholar working on Computer Vision and Pattern Recognition, Business and International Management and Computer Graphics and Computer-Aided Design, having authored 18 papers that have together received 271 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Autonomous Vehicle Technology and Safety (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (210 citations), Safety, Risk, Reliability and Quality (28 citations) and Artificial Intelligence (77 citations). Bing Bai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Bineng Zhong, Yun Fu, Yulun Zhang, Jun Li, Yogesh Balaji, Hans Peter Graf, Rama Chellappa, Martin Renqiang Min, David Grangier and Kilian Q. Weinberger. Their work appears in journals such as IEEE Transactions on Image Processing, Neurocomputing and Computers & Security.
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.