Yao-Chung Fan
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Molecular Biology
- Electrical and Electronic Engineering
- Co-authors
- Arbee L. P. ChenWen-Chih PengPeng‐Wei WangYu-Chun YenHsin-Lan LinShou‐Mei WuChung‐An ChenKuo-Chen Wu
- Topics
- Topic Modeling (13 papers)Natural Language Processing Techniques (9 papers)Human Mobility and Location-Based Analysis (8 papers)
- Cited by
- Artificial IntelligenceComputer Science ApplicationsComputer Vision and Pattern Recognition
- Journals
- IEEE AccessSensors and Actuators B ChemicalIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- TaiwanUnited StatesSouth Korea
In The Last Decade
Yao-Chung Fan
43 papers receiving 336 citations
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 136
- Computer Vision and Pattern Recognition 64
- Computer Networks and Communications 51
- Molecular Biology 49
- Electrical and Electronic Engineering 47
Countries citing papers authored by Yao-Chung Fan
This map shows the geographic impact of Yao-Chung 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 Yao-Chung Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yao-Chung Fan more than expected).
Fields of papers citing papers by Yao-Chung Fan
This network shows the impact of papers produced by Yao-Chung 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 Yao-Chung Fan. The network helps show where Yao-Chung Fan may publish in the future.
Co-authorship network of co-authors of Yao-Chung Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Yao-Chung Fan. A scholar is included among the top collaborators of Yao-Chung 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 Yao-Chung Fan. Yao-Chung 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 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 3 | |
| 10 | 85 | |
| 11 | 11 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 6 | |
| 16 | 5 | |
| 17 | 12 | |
| 18 | Laser processed hydrogenated amorphous silicon for field emission displays | 2 |
| 19 | 1 | |
| 20 | 9 |
About Yao-Chung Fan
Yao-Chung Fan is a scholar working on Transportation, Signal Processing and Artificial Intelligence, having authored 48 papers that have together received 346 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers) and Human Mobility and Location-Based Analysis (8 papers). The work is most often cited by research in Artificial Intelligence (136 citations), Computer Science Applications (22 citations) and Computer Vision and Pattern Recognition (64 citations). Yao-Chung Fan has collaborated with scholars based in Taiwan, United States and South Korea. Frequent co-authors include Arbee L. P. Chen, Wen-Chih Peng, Peng‐Wei Wang, Yu-Chun Yen, Hsin-Lan Lin, Shou‐Mei Wu, Chung‐An Chen, Kuo-Chen Wu, Albert Rizzo and Chia‐Fen Tsai. Their work appears in journals such as IEEE Access, Sensors and Actuators B Chemical and IEEE Transactions on Knowledge and Data Engineering.
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.