Wei Tang
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Statistical and Nonlinear Physics top 10%
- Human-Computer Interaction top 5%
- Co-authors
- Inderjit S. DhillonZhengdong LuGang HuaLe WangNanning ZhengSanping ZhouPeipei SongYing Wu
- Topics
- Human Pose and Action Recognition (22 papers)Video Surveillance and Tracking Methods (16 papers)Anomaly Detection Techniques and Applications (15 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingPattern Recognition
- Partner nations
- United StatesChinaJapan
In The Last Decade
Wei Tang
64 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 134
- Computer Vision and Pattern Recognition 764
- Artificial Intelligence 441
- Biomedical Engineering 168
- Statistical and Nonlinear Physics 91
- Human-Computer Interaction 72
Countries citing papers authored by Wei Tang
This map shows the geographic impact of Wei Tang'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 Wei Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Tang more than expected).
Fields of papers citing papers by Wei Tang
This network shows the impact of papers produced by Wei Tang. 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 Wei Tang. The network helps show where Wei Tang may publish in the future.
Co-authorship network of co-authors of Wei Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Wei Tang. A scholar is included among the top collaborators of Wei Tang 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 Wei Tang. Wei Tang 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 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 0 | |
| 7 | 9 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 8 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 7 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 8 | |
| 17 | 10 | |
| 18 | 6 | |
| 19 | A computational model for simulating the future using a memory timeline | 1 |
| 20 | 4 |
About Wei Tang
Wei Tang is a scholar working on Computer Vision and Pattern Recognition, Health Informatics and Artificial Intelligence, having authored 71 papers that have together received 1.2k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (22 papers), Video Surveillance and Tracking Methods (16 papers) and Anomaly Detection Techniques and Applications (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (764 citations), Computational Mathematics (12 citations) and Artificial Intelligence (441 citations). Wei Tang has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Inderjit S. Dhillon, Zhengdong Lu, Gang Hua, Le Wang, Nanning Zheng, Sanping Zhou, Peipei Song, Ying Wu, Kenji Karako and Qilin Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing 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.