Kevin Lin
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Aerospace Engineering
- Media Technology top 10%
- Computational Mechanics
- Co-authors
- Chu‐Song ChenHuei‐Fang YangJiwen LuJie ZhouMing–Ting SunJen-Hao HsiaoKuan-Hsien LiuKun Luo
- Topics
- Advanced Image and Video Retrieval Techniques (7 papers)Domain Adaptation and Few-Shot Learning (4 papers)Robotics and Sensor-Based Localization (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Neural Networks and Learning SystemsIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- TaiwanUnited StatesUnited Kingdom
In The Last Decade
Kevin Lin
12 papers receiving 642 citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 599
- Artificial Intelligence 121
- Aerospace Engineering 59
- Media Technology 43
- Computational Mechanics 18
Countries citing papers authored by Kevin Lin
This map shows the geographic impact of Kevin 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 Kevin Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Lin more than expected).
Fields of papers citing papers by Kevin Lin
This network shows the impact of papers produced by Kevin 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 Kevin Lin. The network helps show where Kevin Lin may publish in the future.
Co-authorship network of co-authors of Kevin Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Lin. A scholar is included among the top collaborators of Kevin Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kevin Lin. Kevin Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 50 | |
| 5 | Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation. | 3 |
| 6 | 3 | |
| 7 | 51 | |
| 8 | 224 | |
| 9 | Learning Compact Binary Descriptors with Unsupervised Deep Neural Networksbreakdown → | 257 |
| 10 | 12 | |
| 11 | 48 | |
| 12 | 1 |
About Kevin Lin
Kevin Lin is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence, having authored 12 papers that have together received 655 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (7 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Robotics and Sensor-Based Localization (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (599 citations), Media Technology (43 citations) and Artificial Intelligence (121 citations). Kevin Lin has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Chu‐Song Chen, Huei‐Fang Yang, Jiwen Lu, Jie Zhou, Ming–Ting Sun, Jen-Hao Hsiao, Kuan-Hsien Liu, Kun Luo, Yinpeng Chen and Zicheng Liu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Circuits and Systems for Video Technology.
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.