Luojun Lin
Impact in
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- Face recognition and analysis
- Human Pose and Action Recognition
- Face and Expression Recognition
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
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- Evolutionary Psychology and Human Behavior
Papers in
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- Face recognition and analysis 8
- Multimodal Machine Learning Applications 8
- Advanced Neural Network Applications 6
- Human Pose and Action Recognition 5
- Advanced Image and Video Retrieval Techniques 4
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- Domain Adaptation and Few-Shot Learning 11
- Co-authors
- Lianwen Jin (10 shared papers)Lingyu Liang (5 shared papers)Tasweer Ahmad (3 shared papers)Mengru Li (2 shared papers)Songxuan Lai (3 shared papers)Weijie Chen (10 shared papers)Xin Zhang (1 shared paper)Shicai Yang (7 shared papers)
In The Last Decade
Luojun Lin
26 papers receiving 505 citations
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 392
- Experimental and Cognitive Psychology 106
- Human-Computer Interaction 37
- Artificial Intelligence 181
- Marketing 32
Countries citing papers authored by Luojun Lin
This map shows the geographic impact of Luojun 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 Luojun Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luojun Lin more than expected).
Fields of papers citing papers by Luojun Lin
This network shows the impact of papers produced by Luojun 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 Luojun Lin. The network helps show where Luojun Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Luojun 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 129 | |
| 2 | 2021 | 95 | |
| 3 | 2019 | 33 | |
| 4 | 2022 | 32 | |
| 5 | 2019 | 30 | |
| 6 | 2020 | 27 | |
| 7 | 2019 | 26 | |
| 8 | 2020 | 23 | |
| 9 | 2021 | 22 | |
| 10 | 2022 | 17 | |
| 11 | 2018 | 12 | |
| 12 | 2017 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2024 | 8 | |
| 15 | 2022 | 8 | |
| 16 | 2024 | 5 | |
| 17 | 2023 | 5 | |
| 18 | 2023 | 4 | |
| 19 | 2023 | 3 | |
| 20 | 2023 | 3 |
About Luojun Lin
Luojun Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Experimental and Cognitive Psychology, Dermatology and Cognitive Neuroscience, having authored 27 papers that have together received 512 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (11 papers), Face recognition and analysis (8 papers), Multimodal Machine Learning Applications (8 papers), Evolutionary Psychology and Human Behavior (7 papers), Advanced Neural Network Applications (6 papers), Human Pose and Action Recognition (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Facial Rejuvenation and Surgery Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (392 citations), Experimental and Cognitive Psychology (106 citations), Human-Computer Interaction (37 citations), Artificial Intelligence (181 citations) and Marketing (32 citations). Luojun Lin has collaborated with scholars based in China, Pakistan and Hong Kong. Frequent co-authors include Lianwen Jin, Lingyu Liang, Tasweer Ahmad, Mengru Li, Songxuan Lai, Weijie Chen, Xin Zhang, Shicai Yang, Di Xie and Yueting Zhuang. Their work appears in journals such as Neurocomputing, Knowledge-Based Systems, IEEE Access, Pattern Recognition and IEEE Transactions on Affective Computing.
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.