Chin‐Chia Michael Yeh
- Signal Processing top 0.5%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Economics and Econometrics top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Eamonn KeoghYan ZhuAbdullah MueenYifei DingLiudmila UlanovaDiego Furtado SilvaHoang Anh DauZachary Zimmerman
- Topics
- Time Series Analysis and Forecasting (21 papers)Music and Audio Processing (15 papers)Anomaly Detection Techniques and Applications (10 papers)
- Journals
- IEEE Transactions on Visualization and Computer GraphicsIEEE Transactions on MultimediaProceedings of the VLDB Endowment
- Partner nations
- United StatesTaiwanBrazil
In The Last Decade
Chin‐Chia Michael Yeh
48 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Signal Processing 761
- Artificial Intelligence 715
- Computer Vision and Pattern Recognition 235
- Economics and Econometrics 176
- Computer Networks and Communications 134
Countries citing papers authored by Chin‐Chia Michael Yeh
This map shows the geographic impact of Chin‐Chia Michael Yeh'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 Chin‐Chia Michael Yeh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chin‐Chia Michael Yeh more than expected).
Fields of papers citing papers by Chin‐Chia Michael Yeh
This network shows the impact of papers produced by Chin‐Chia Michael Yeh. 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 Chin‐Chia Michael Yeh. The network helps show where Chin‐Chia Michael Yeh may publish in the future.
Co-authorship network of co-authors of Chin‐Chia Michael Yeh
This figure shows the co-authorship network connecting the top 25 collaborators of Chin‐Chia Michael Yeh. A scholar is included among the top collaborators of Chin‐Chia Michael Yeh 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 Chin‐Chia Michael Yeh. Chin‐Chia Michael Yeh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 5 | |
| 7 | 9 | |
| 8 | 4 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 20 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 30 | |
| 15 | 2 | |
| 16 | 19 | |
| 17 | 36 | |
| 18 | 24 | |
| 19 | 7 | |
| 20 | 34 |
About Chin‐Chia Michael Yeh
Chin‐Chia Michael Yeh is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 52 papers that have together received 1.2k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (21 papers), Music and Audio Processing (15 papers) and Anomaly Detection Techniques and Applications (10 papers). The work is most often cited by research in Signal Processing (761 citations), Artificial Intelligence (715 citations) and Computer Vision and Pattern Recognition (235 citations). Chin‐Chia Michael Yeh has collaborated with scholars based in United States, Taiwan and Brazil. Frequent co-authors include Eamonn Keogh, Yan Zhu, Abdullah Mueen, Yifei Ding, Liudmila Ulanova, Diego Furtado Silva, Hoang Anh Dau, Zachary Zimmerman, Nurjahan Begum and Yi‐Hsuan Yang. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Multimedia and Proceedings of the VLDB Endowment.
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.