Nick C. Tang
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design top 5%
- Biomedical Engineering
- Signal Processing
- Co-authors
- Timothy K. ShihJenq–Neng HwangYen‐Yu LinHong-Yuan Mark LiaoChiou-Ting HsuJason C. HungChih-Wen SuMing-Fang Weng
- Topics
- Generative Adversarial Networks and Image Synthesis (13 papers)Human Pose and Action Recognition (13 papers)Advanced Vision and Imaging (11 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignHuman-Computer Interaction
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Circuits and Systems for Video TechnologyIEEE Transactions on Visualization and Computer Graphics
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Nick C. Tang
30 papers receiving 348 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 318
- Artificial Intelligence 60
- Computer Graphics and Computer-Aided Design 48
- Biomedical Engineering 33
- Signal Processing 23
Countries citing papers authored by Nick C. Tang
This map shows the geographic impact of Nick C. 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 Nick C. Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nick C. Tang more than expected).
Fields of papers citing papers by Nick C. Tang
This network shows the impact of papers produced by Nick C. 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 Nick C. Tang. The network helps show where Nick C. Tang may publish in the future.
Co-authorship network of co-authors of Nick C. Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Nick C. Tang. A scholar is included among the top collaborators of Nick C. 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 Nick C. Tang. Nick C. 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 | 12 | |
| 3 | 22 | |
| 4 | 9 | |
| 5 | 8 | |
| 6 | 5 | |
| 7 | 56 | |
| 8 | 8 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 30 | |
| 12 | 1 | |
| 13 | 0 | |
| 14 | 8 | |
| 15 | 7 | |
| 16 | 33 | |
| 17 | 5 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 14 |
About Nick C. Tang
Nick C. Tang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Human-Computer Interaction, having authored 31 papers that have together received 368 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (13 papers), Human Pose and Action Recognition (13 papers) and Advanced Vision and Imaging (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (318 citations), Computer Graphics and Computer-Aided Design (48 citations) and Human-Computer Interaction (21 citations). Nick C. Tang has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Timothy K. Shih, Jenq–Neng Hwang, Yen‐Yu Lin, Hong-Yuan Mark Liao, Chiou-Ting Hsu, Jason C. Hung, Chih-Wen Su, Ming-Fang Weng, Yu-Shuen Wang and Hung‐Kuo Chu. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Visualization and Computer Graphics.
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.