Y.S. Gan
Impact in
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- Emotion and Mood Recognition
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- Human Pose and Action Recognition
- Face and Expression Recognition
- Face recognition and analysis
Papers in
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- Face and Expression Recognition 4
- Human Pose and Action Recognition 3
- Face recognition and analysis 3
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- Industrial Vision Systems and Defect Detection 11
- Co-authors
- Sze‐Teng Liong (32 shared papers)Yen‐Chang Huang (8 shared papers)Wei‐Chuen Yau (6 shared papers)Kunhong Liu (7 shared papers)Shih-Yuan Wang (10 shared papers)Qiushi Jin (2 shared papers)Kim Hoong Ng (1 shared paper)Chin Kui Cheng (1 shared paper)
In The Last Decade
Y.S. Gan
34 papers receiving 561 citations
Peers
Comparison fields: 5 of 79
- Experimental and Cognitive Psychology 218
- Computer Vision and Pattern Recognition 256
- Industrial and Manufacturing Engineering 121
- Urban Studies 55
- Human-Computer Interaction 53
Countries citing papers authored by Y.S. Gan
This map shows the geographic impact of Y.S. Gan'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 Y.S. Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Y.S. Gan more than expected).
Fields of papers citing papers by Y.S. Gan
This network shows the impact of papers produced by Y.S. Gan. 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 Y.S. Gan. The network helps show where Y.S. Gan may publish in the future.
Co-authors
The 25 scholars most cited alongside Y.S. Gan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 211 | |
| 2 | 2020 | 45 | |
| 3 | 2020 | 43 | |
| 4 | 2020 | 26 | |
| 5 | 2021 | 24 | |
| 6 | 2020 | 23 | |
| 7 | 2021 | 21 | |
| 8 | 2023 | 19 | |
| 9 | 2019 | 18 | |
| 10 | 2018 | 15 | |
| 11 | 2020 | 13 | |
| 12 | 2022 | 13 | |
| 13 | 2023 | 9 | |
| 14 | 2023 | 9 | |
| 15 | 2022 | 9 | |
| 16 | 2022 | 8 | |
| 17 | 2023 | 7 | |
| 18 | 2020 | 7 | |
| 19 | 2020 | 6 | |
| 20 | 2022 | 6 |
About Y.S. Gan
Y.S. Gan is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Computational Mechanics, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 39 papers that have together received 565 indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (11 papers), Emotion and Mood Recognition (6 papers), Surface Roughness and Optical Measurements (5 papers), Face and Expression Recognition (4 papers), Spectroscopy and Chemometric Analyses (4 papers), 3D Surveying and Cultural Heritage (4 papers), Human Pose and Action Recognition (3 papers) and Face recognition and analysis (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (218 citations), Computer Vision and Pattern Recognition (256 citations), Industrial and Manufacturing Engineering (121 citations), Urban Studies (55 citations) and Human-Computer Interaction (53 citations). Y.S. Gan has collaborated with scholars based in Taiwan, Malaysia and China. Frequent co-authors include Sze‐Teng Liong, Yen‐Chang Huang, Wei‐Chuen Yau, Kunhong Liu, Shih-Yuan Wang, Qiushi Jin, Kim Hoong Ng, Chin Kui Cheng, Hanzhe Zhang and Yi‐Chen Chiang. Their work appears in journals such as Expert Systems with Applications, Journal of Ambient Intelligence and Humanized Computing, Neurocomputing, Journal of Food Process Engineering and Journal of Food 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.