Kuo‐Chin Fan
- Computer Vision and Pattern Recognition top 0.5%
- Signal Processing top 1%
- Media Technology top 0.5%
- Artificial Intelligence top 5%
- Information Systems top 5%
- Co-authors
- Chih-Lung LinChin-Chuan HanLuo-Wei TsaiJun‐Wei HsiehYuan-Kai WangChin‐Chuan HanJun-Wei HsiehYing-Nong Chen
- Topics
- Image Retrieval and Classification Techniques (35 papers)Advanced Image and Video Retrieval Techniques (29 papers)Handwritten Text Recognition Techniques (23 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Image Processing
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Kuo‐Chin Fan
138 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 130
- Computer Vision and Pattern Recognition 2.0k
- Signal Processing 754
- Media Technology 465
- Artificial Intelligence 268
- Information Systems 252
Countries citing papers authored by Kuo‐Chin Fan
This map shows the geographic impact of Kuo‐Chin Fan'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 Kuo‐Chin Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuo‐Chin Fan more than expected).
Fields of papers citing papers by Kuo‐Chin Fan
This network shows the impact of papers produced by Kuo‐Chin Fan. 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 Kuo‐Chin Fan. The network helps show where Kuo‐Chin Fan may publish in the future.
Co-authorship network of co-authors of Kuo‐Chin Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Kuo‐Chin Fan. A scholar is included among the top collaborators of Kuo‐Chin Fan 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 Kuo‐Chin Fan. Kuo‐Chin Fan 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 | 5 | |
| 3 | 22 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 29 | |
| 7 | 17 | |
| 8 | Palmprint verification using gradient maps and support vector machines | 3 |
| 9 | 10 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 25 | |
| 13 | 37 | |
| 14 | 3 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 1 | |
| 18 | 6 | |
| 19 | Error-Correcting Isomorphism of Directed Graphs by Genetic-Based Search. | 2 |
| 20 | 8 |
About Kuo‐Chin Fan
Kuo‐Chin Fan is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 146 papers that have together received 2.8k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (35 papers), Advanced Image and Video Retrieval Techniques (29 papers) and Handwritten Text Recognition Techniques (23 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.0k citations), Signal Processing (754 citations) and Media Technology (465 citations). Kuo‐Chin Fan has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Chih-Lung Lin, Chin-Chuan Han, Luo-Wei Tsai, Jun‐Wei Hsieh, Yuan-Kai Wang, Chin‐Chuan Han, Jun-Wei Hsieh, Ying-Nong Chen, Hong-Yuan Mark Liao and An-Bang Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing 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.