Chun-Ming Tsai
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Artificial Intelligence
- Atomic and Molecular Physics, and Optics
- Automotive Engineering
- Co-authors
- Zong-Mu YehHsi-Jian LeeFrank Y. ShihYen‐Ju WuYuan-Fang WangYen-Yi WuJun‐Wei HsiehJun-Wei Hsieh
- Topics
- Advanced Neural Network Applications (9 papers)Video Surveillance and Tracking Methods (7 papers)Handwritten Text Recognition Techniques (6 papers)
- Journals
- IEEE Transactions on Image ProcessingPattern RecognitionIEEE Transactions on Consumer Electronics
- Partner nations
- TaiwanUnited States
In The Last Decade
Chun-Ming Tsai
25 papers receiving 340 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 270
- Media Technology 122
- Artificial Intelligence 26
- Atomic and Molecular Physics, and Optics 21
- Automotive Engineering 18
Countries citing papers authored by Chun-Ming Tsai
This map shows the geographic impact of Chun-Ming Tsai'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 Chun-Ming Tsai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun-Ming Tsai more than expected).
Fields of papers citing papers by Chun-Ming Tsai
This network shows the impact of papers produced by Chun-Ming Tsai. 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 Chun-Ming Tsai. The network helps show where Chun-Ming Tsai may publish in the future.
Co-authorship network of co-authors of Chun-Ming Tsai
This figure shows the co-authorship network connecting the top 25 collaborators of Chun-Ming Tsai. A scholar is included among the top collaborators of Chun-Ming Tsai 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 Chun-Ming Tsai. Chun-Ming Tsai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 21 | |
| 6 | 11 | |
| 7 | 10 | |
| 8 | 1 | |
| 9 | 22 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | 4 | |
| 13 | 34 | |
| 14 | 2 | |
| 15 | 3 | |
| 16 | 5 | |
| 17 | 0 | |
| 18 | 17 | |
| 19 | 17 | |
| 20 | 86 |
About Chun-Ming Tsai
Chun-Ming Tsai is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Automotive Engineering, having authored 27 papers that have together received 354 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Video Surveillance and Tracking Methods (7 papers) and Handwritten Text Recognition Techniques (6 papers). The work is most often cited by research in Media Technology (122 citations), Computer Vision and Pattern Recognition (270 citations) and Automotive Engineering (18 citations). Chun-Ming Tsai has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Zong-Mu Yeh, Hsi-Jian Lee, Frank Y. Shih, Yen‐Ju Wu, Yuan-Fang Wang, Yen-Yi Wu, Jun‐Wei Hsieh, Jun-Wei Hsieh, Ming‐Ching Chang and Yuan Wang. Their work appears in journals such as IEEE Transactions on Image Processing, Pattern Recognition and IEEE Transactions on Consumer Electronics.
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.