Chi Lin
Impact in
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- Image Retrieval and Classification Techniques
- Face recognition and analysis
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Human-Computer Interaction top 5%
- Hand Gesture Recognition Systems
Papers in
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- Image Enhancement Techniques 3
- Human Pose and Action Recognition 3
- Face recognition and analysis 3
- Image and Signal Denoising Methods 2
- Face and Expression Recognition 2
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- Biometric Identification and Security 3
- Co-authors
- Rama Chellappa (1 shared paper)Jun Wan (5 shared papers)Stan Z. Li (5 shared papers)Yanyan Liang (4 shared papers)Guodong Guo (3 shared papers)Danna Gurari (2 shared papers)Isabelle Guyon (2 shared papers)Anhong Guo (1 shared paper)
- Journals
- IEEE Transactions on Cybernetics (2 papers)Proceedings of the ACM on Human-Computer Interaction (1 paper)The Visual Computer (1 paper)Symmetry (1 paper)Machine Vision and Applications (1 paper)
- Partner nations
- United StatesChinaMacao
In The Last Decade
Chi Lin
12 papers receiving 319 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 264
- Human-Computer Interaction 60
- Signal Processing 73
- Human Factors and Ergonomics 7
- Artificial Intelligence 67
Countries citing papers authored by Chi Lin
This map shows the geographic impact of Chi Lin'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 Chi Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi Lin more than expected).
Fields of papers citing papers by Chi Lin
This network shows the impact of papers produced by Chi Lin. 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 Chi Lin. The network helps show where Chi Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Chi Lin, 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 | 1987 | 105 | |
| 2 | 2019 | 63 | |
| 3 | 2019 | 62 | |
| 4 | 2020 | 30 | |
| 5 | 2018 | 24 | |
| 6 | 2019 | 11 | |
| 7 | 2019 | 10 | |
| 8 | 2022 | 9 | |
| 9 | 2022 | 7 | |
| 10 | 2018 | 6 | |
| 11 | 2021 | 4 | |
| 12 | 2024 | 3 |
About Chi Lin
Chi Lin is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Human-Computer Interaction, Biomedical Engineering and Media Technology, having authored 12 papers that have together received 334 indexed citations. Recurring topics across this work include Hand Gesture Recognition Systems (3 papers), Image Enhancement Techniques (3 papers), Human Pose and Action Recognition (3 papers), Face recognition and analysis (3 papers), Gait Recognition and Analysis (3 papers), Biometric Identification and Security (3 papers), Image and Signal Denoising Methods (2 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (264 citations), Human-Computer Interaction (60 citations), Signal Processing (73 citations), Human Factors and Ergonomics (7 citations) and Artificial Intelligence (67 citations). Chi Lin has collaborated with scholars based in United States, China and Macao. Frequent co-authors include Rama Chellappa, Jun Wan, Stan Z. Li, Yanyan Liang, Guodong Guo, Danna Gurari, Isabelle Guyon, Anhong Guo, Abigale Stangl and Sérgio Escalera. Their work appears in journals such as IEEE Transactions on Cybernetics, Proceedings of the ACM on Human-Computer Interaction, The Visual Computer, Symmetry and Machine Vision and Applications.
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.