Jun Tao
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Computer Graphics and Computer-Aided Design top 2%
- Signal Processing top 10%
- Computational Mechanics top 10%
- Co-authors
- Chaoli WangJun HanChing-Kuang SheneJun MaNitesh V. ChawlaHanqi GuoChao HuangZhisheng Zhang
- Topics
- Data Visualization and Analytics (18 papers)Computer Graphics and Visualization Techniques (16 papers)Video Analysis and Summarization (8 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionSignal Processing
- Journals
- Proceedings of the National Academy of SciencesAnalytical ChemistryThe Science of The Total Environment
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Jun Tao
56 papers receiving 557 citations
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 298
- Artificial Intelligence 114
- Computer Graphics and Computer-Aided Design 112
- Signal Processing 78
- Computational Mechanics 64
Countries citing papers authored by Jun Tao
This map shows the geographic impact of Jun Tao'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 Jun Tao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Tao more than expected).
Fields of papers citing papers by Jun Tao
This network shows the impact of papers produced by Jun Tao. 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 Jun Tao. The network helps show where Jun Tao may publish in the future.
Co-authorship network of co-authors of Jun Tao
This figure shows the co-authorship network connecting the top 25 collaborators of Jun Tao. A scholar is included among the top collaborators of Jun Tao 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 Jun Tao. Jun Tao 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 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 11 | |
| 10 | 8 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | 25 | |
| 14 | 3 | |
| 15 | 6 | |
| 16 | 5 | |
| 17 | 32 | |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 58 |
About Jun Tao
Jun Tao is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Signal Processing, having authored 60 papers that have together received 570 indexed citations. Recurring topics across this work include Data Visualization and Analytics (18 papers), Computer Graphics and Visualization Techniques (16 papers) and Video Analysis and Summarization (8 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (112 citations), Computer Vision and Pattern Recognition (298 citations) and Signal Processing (78 citations). Jun Tao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Chaoli Wang, Jun Han, Ching-Kuang Shene, Jun Ma, Nitesh V. Chawla, Hanqi Guo, Chao Huang, Zhisheng Zhang, Jun Ma and Danny Z. Chen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Analytical Chemistry and The Science of The Total Environment.
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.