Lin Geng Foo
Impact in
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Multimodal Machine Learning Applications
- Human-Computer Interaction top 10%
- Hand Gesture Recognition Systems
Papers in
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- Human Pose and Action Recognition 7
- Advanced Neural Network Applications 5
- Advanced Vision and Imaging 3
- Video Surveillance and Tracking Methods 2
- Generative Adversarial Networks and Image Synthesis 2
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- Anomaly Detection Techniques and Applications 6
- Adversarial Robustness in Machine Learning 2
- Domain Adaptation and Few-Shot Learning 2
- Co-authors
- Jun Liu (12 shared papers)Hossein Rahmani (6 shared papers)Qiuhong Ke (4 shared papers)Jia Gong (3 shared papers)Zhipeng Fan (4 shared papers)Tianjiao Li (2 shared papers)Hossein Rahmani (2 shared papers)Yixuan He (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)ACM Computing Surveys (1 paper)IEEE Transactions on Multimedia (1 paper)Monash University Research Portal (Monash University) (2 papers)
- Partner nations
- SingaporeUnited KingdomAustralia
In The Last Decade
Lin Geng Foo
13 papers receiving 173 citations
Peers
Comparison fields: 5 of 32
- Computer Vision and Pattern Recognition 146
- Human-Computer Interaction 35
- Artificial Intelligence 61
- Biomedical Engineering 54
- Computational Mechanics 21
Countries citing papers authored by Lin Geng Foo
This map shows the geographic impact of Lin Geng Foo'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 Lin Geng Foo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Geng Foo more than expected).
Fields of papers citing papers by Lin Geng Foo
This network shows the impact of papers produced by Lin Geng Foo. 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 Lin Geng Foo. The network helps show where Lin Geng Foo may publish in the future.
Co-authors
The 18 scholars most cited alongside Lin Geng Foo, 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 | 2023 | 75 | |
| 2 | 2023 | 30 | |
| 3 | 2024 | 21 | |
| 4 | 2023 | 16 | |
| 5 | 2023 | 9 | |
| 6 | 2023 | 4 | |
| 7 | 2024 | 4 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 3 | |
| 10 | 2025 | 3 | |
| 11 | 2023 | 3 | |
| 12 | 2025 | 2 | |
| 13 | 2023 | 1 |
About Lin Geng Foo
Lin Geng Foo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, General Health Professions, Control and Systems Engineering and Signal Processing, having authored 13 papers that have together received 175 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (7 papers), Anomaly Detection Techniques and Applications (6 papers), Advanced Neural Network Applications (5 papers), Advanced Vision and Imaging (3 papers), Video Surveillance and Tracking Methods (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (146 citations), Human-Computer Interaction (35 citations), Artificial Intelligence (61 citations), Biomedical Engineering (54 citations) and Computational Mechanics (21 citations). Lin Geng Foo has collaborated with scholars based in Singapore, United Kingdom and Australia. Frequent co-authors include Jun Liu, Hossein Rahmani, Qiuhong Ke, Jia Gong, Zhipeng Fan, Tianjiao Li, Hossein Rahmani, Yixuan He, Yujun Cai and Jianhong Pan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Computing Surveys, IEEE Transactions on Multimedia and Monash University Research Portal (Monash University).
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.