Ming Tang
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Aerospace Engineering top 5%
- Media Technology top 2%
- Electrical and Electronic Engineering
- Topics
- Video Surveillance and Tracking Methods (40 papers)Advanced Neural Network Applications (22 papers)Human Pose and Action Recognition (18 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Cleaner ProductionIEEE Transactions on Image Processing
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Ming Tang
101 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Computer Vision and Pattern Recognition 1.7k
- Artificial Intelligence 558
- Aerospace Engineering 263
- Media Technology 216
- Electrical and Electronic Engineering 154
Countries citing papers authored by Ming Tang
This map shows the geographic impact of Ming 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 Ming Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Tang more than expected).
Fields of papers citing papers by Ming Tang
This network shows the impact of papers produced by Ming 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 Ming Tang. The network helps show where Ming Tang may publish in the future.
Co-authorship network of co-authors of Ming Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Ming Tang. A scholar is included among the top collaborators of Ming 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 Ming Tang. Ming 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 | 3 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | 22 | |
| 9 | 9 | |
| 10 | 81 | |
| 11 | 2 | |
| 12 | 18 | |
| 13 | 14 | |
| 14 | 7 | |
| 15 | 10 | |
| 16 | 216 | |
| 17 | 32 | |
| 18 | 22 | |
| 19 | Learning Features with Differentiable Closed-Form Solver for Tracking | 1 |
| 20 | 4 |
About Ming Tang
Ming Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Architecture, having authored 110 papers that have together received 2.3k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (40 papers), Advanced Neural Network Applications (22 papers) and Human Pose and Action Recognition (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Media Technology (216 citations) and Artificial Intelligence (558 citations). Ming Tang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jinqiao Wang, Yingying Chen, Hanqing Lu, Jiayi Feng, Yancheng Bai, Bingke Zhu, Zhengtao Yu, Fang Qi, Weijiang Li and Chaoyang Zhao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Cleaner Production and IEEE Transactions on Image Processing.
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.