Eric Sung
- Human-Computer Interaction top 1%
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- Face recognition and analysis 27
- Face and Expression Recognition 15
- Advanced Vision and Imaging 9
- Signal Processing top 2%
- Ophthalmology top 2%
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- 3D Shape Modeling and Analysis 15
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- Cardiac electrophysiology and arrhythmias 14
- Cardiac Arrhythmias and Treatments 11
- Cardiovascular Effects of Exercise 7
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- Human Motion and Animation 8
Eric Sung
71 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 142
- Human-Computer Interaction 251
- Computer Vision and Pattern Recognition 803
- Signal Processing 325
- Ophthalmology 236
- Radiology, Nuclear Medicine and Imaging 256
Countries citing papers authored by Eric Sung
This map shows the geographic impact of Eric Sung'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 Eric Sung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Sung more than expected).
Fields of papers citing papers by Eric Sung
This network shows the impact of papers produced by Eric Sung. 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 Eric Sung. The network helps show where Eric Sung may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Eric Sung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2023 | 16 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 10 | |
| 5 | 2022 | 9 | |
| 6 | 2022 | 37 | |
| 7 | 2022 | 4 | |
| 8 | 2022 | 5 | |
| 9 | 2021 | 34 | |
| 10 | 2021 | 18 | |
| 11 | 2021 | 8 | |
| 12 | 2021 | 13 | |
| 13 | 2021 | 11 | |
| 14 | 2020 | 3 | |
| 15 | 2010 | 15 | |
| 16 | 2006 | 6 | |
| 17 | Anatomy-based human face reconstruction using multi-layer deformation | 2005 | 2 |
| 18 | 2003 | 2 | |
| 19 | 2002 | 0 | |
| 20 | On Eye Gaze Determination via Iris Contour. | 2000 | 3 |
About Eric Sung
Eric Sung is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Human-Computer Interaction, Cardiology and Cardiovascular Medicine and Computational Mechanics, having authored 74 papers that have together received 1.7k indexed citations. Recurring topics across this work include Face recognition and analysis (27 papers), Face and Expression Recognition (15 papers), 3D Shape Modeling and Analysis (15 papers), Cardiac electrophysiology and arrhythmias (14 papers), Cardiac Arrhythmias and Treatments (11 papers), Advanced Vision and Imaging (9 papers), Human Motion and Animation (8 papers) and Cardiovascular Effects of Exercise (7 papers). The work is most often cited by research in Human-Computer Interaction (251 citations), Computer Vision and Pattern Recognition (803 citations), Signal Processing (325 citations), Ophthalmology (236 citations) and Radiology, Nuclear Medicine and Imaging (256 citations). Eric Sung has collaborated with scholars based in Singapore, United States and Canada. Frequent co-authors include Jian-Gang Wang, Lei Wang, Xuchun Li, Wei‐Yun Yau, Jiangang Wang, Edmond C. Prakash, Ronda Venkateswarlu, Ce Zheng, O. Chutatape and Juan Xu. Their work appears in journals such as Heart Rhythm, Journal of Visual Languages & Computing, Pattern Recognition Letters, Image and Vision Computing and Pattern Recognition.
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.