Yung-Fu Chen
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Epidemiology
- Cardiology and Cardiovascular Medicine
- Co-authors
- Tan-Hsu TanHsuan‐Hung LinYung‐Kuan ChanWei‐Sheng ChungMunkhjargal GochooCheng‐Li LinChia‐Hung KaoTsu‐Yi Hsieh
- Topics
- Machine Learning in Healthcare (5 papers)Sexual function and dysfunction studies (4 papers)Heart Rate Variability and Autonomic Control (4 papers)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Yung-Fu Chen
60 papers receiving 924 citations
Peers
Comparison fields: 5 of 143
- Computer Vision and Pattern Recognition 236
- Artificial Intelligence 168
- Biomedical Engineering 129
- Epidemiology 111
- Cardiology and Cardiovascular Medicine 102
Countries citing papers authored by Yung-Fu Chen
This map shows the geographic impact of Yung-Fu Chen'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 Yung-Fu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yung-Fu Chen more than expected).
Fields of papers citing papers by Yung-Fu Chen
This network shows the impact of papers produced by Yung-Fu Chen. 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 Yung-Fu Chen. The network helps show where Yung-Fu Chen may publish in the future.
Co-authorship network of co-authors of Yung-Fu Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Yung-Fu Chen. A scholar is included among the top collaborators of Yung-Fu Chen 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 Yung-Fu Chen. Yung-Fu Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 22 | |
| 3 | 19 | |
| 4 | 30 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 6 | |
| 8 | 15 | |
| 9 | 14 | |
| 10 | 5 | |
| 11 | 63 | |
| 12 | 6 | |
| 13 | 7 | |
| 14 | True color image steganography using palette and minimum spanning tree | 7 |
| 15 | 20 | |
| 16 | Implementation of an image retrieval system using wavelet decomposition and gradient variation | 4 |
| 17 | 5 | |
| 18 | Implementation of a central laboratory with consolidated laboratory network for central Taiwan national hospital union | 1 |
| 19 | Decomposition of Control Signals for Saccade and Vergence Eye Movements Using Independent Component Analysis | 1 |
| 20 | 11 |
About Yung-Fu Chen
Yung-Fu Chen is a scholar working on Health Information Management, Internal Medicine and Computer Vision and Pattern Recognition, having authored 61 papers that have together received 968 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), Sexual function and dysfunction studies (4 papers) and Heart Rate Variability and Autonomic Control (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (236 citations), Health Information Management (42 citations) and Health Informatics (11 citations). Yung-Fu Chen has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Tan-Hsu Tan, Hsuan‐Hung Lin, Yung‐Kuan Chan, Wei‐Sheng Chung, Munkhjargal Gochoo, Cheng‐Li Lin, Chia‐Hung Kao, Tsu‐Yi Hsieh, J.S. Taur and Yen‐Ping Chu. Their work appears in journals such as Scientific Reports, Sensors and Information Sciences.
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.