Kun-Yu Lin
Impact in
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- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
Papers in
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- Anomaly Detection Techniques and Applications 7
- Domain Adaptation and Few-Shot Learning 5
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- Human Pose and Action Recognition 7
- Advanced Neural Network Applications 4
- Video Surveillance and Tracking Methods 4
- Multimodal Machine Learning Applications 3
- Co-authors
- Wei‐Shi Zheng (13 shared papers)Yaowei Wang (2 shared papers)J. Andy (1 shared paper)Carl K. Chang (1 shared paper)Chih‐Lin Hu (2 shared papers)Chang‐Dong Wang (4 shared papers)Ling Huang (3 shared papers)Xiao-Ming Wu (1 shared paper)
In The Last Decade
Kun-Yu Lin
21 papers receiving 325 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Computer Vision and Pattern Recognition 144
- Computer Science Applications 29
- Media Technology 36
- Artificial Intelligence 125
- Transportation 17
Countries citing papers authored by Kun-Yu Lin
This map shows the geographic impact of Kun-Yu 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 Kun-Yu Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun-Yu Lin more than expected).
Fields of papers citing papers by Kun-Yu Lin
This network shows the impact of papers produced by Kun-Yu 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 Kun-Yu Lin. The network helps show where Kun-Yu Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun-Yu 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
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition Hit paper breakdown → | 2023 | 152 |
| 2 | 2022 | 39 | |
| 3 | 2021 | 32 | |
| 4 | 2023 | 18 | |
| 5 | 2019 | 17 | |
| 6 | 2020 | 11 | |
| 7 | 2023 | 11 | |
| 8 | 2022 | 9 | |
| 9 | 2018 | 8 | |
| 10 | 2022 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2017 | 3 | |
| 13 | 2023 | 3 | |
| 14 | 2024 | 2 | |
| 15 | 2024 | 2 | |
| 16 | 2023 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2018 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2025 | 1 |
About Kun-Yu Lin
Kun-Yu Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering and Statistical and Nonlinear Physics, having authored 24 papers that have together received 330 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (7 papers), Anomaly Detection Techniques and Applications (7 papers), Domain Adaptation and Few-Shot Learning (5 papers), Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (4 papers), Multimodal Machine Learning Applications (3 papers), Robot Manipulation and Learning (3 papers) and Gait Recognition and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (144 citations), Computer Science Applications (29 citations), Media Technology (36 citations), Artificial Intelligence (125 citations) and Transportation (17 citations). Kun-Yu Lin has collaborated with scholars based in China, Taiwan and Australia. Frequent co-authors include Wei‐Shi Zheng, Yaowei Wang, J. Andy, Carl K. Chang, Chih‐Lin Hu, Chang‐Dong Wang, Ling Huang, Xiao-Ming Wu, Longbing Cao and Zelin Chen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia, IEEE Transactions on Services Computing and Information Sciences.
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.