Yun Li
Impact in
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- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
Papers in
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- Topic Modeling 23
- Natural Language Processing Techniques 16
- Text and Document Classification Technologies 15
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- Face and Expression Recognition 9
- Image Enhancement Techniques 9
- Co-authors
- Yunhao Yuan (37 shared papers)Jipeng Qiang (28 shared papers)Xindong Wu (14 shared papers)Yujie Li (13 shared papers)Seiichi Serikawa (10 shared papers)Yi Zhu (23 shared papers)Huimin Lu (7 shared papers)Jianru Li (4 shared papers)
- Journals
- IEEE Access (6 papers)Frontiers of Computer Science (4 papers)Applied Intelligence (3 papers)Applied Sciences (2 papers)Information Sciences (2 papers)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Yun Li
97 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 148
- Computer Vision and Pattern Recognition 405
- Artificial Intelligence 523
- Media Technology 141
- General Social Sciences 50
- Information Systems 222
Countries citing papers authored by Yun Li
This map shows the geographic impact of Yun Li'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 Yun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Li more than expected).
Fields of papers citing papers by Yun Li
This network shows the impact of papers produced by Yun Li. 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 Yun Li. The network helps show where Yun Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Yun Li, 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 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 207 | |
| 2 | 2016 | 151 | |
| 3 | 2016 | 135 | |
| 4 | 2016 | 49 | |
| 5 | 2020 | 48 | |
| 6 | 2016 | 45 | |
| 7 | 2013 | 39 | |
| 8 | 2016 | 32 | |
| 9 | 2017 | 31 | |
| 10 | 2017 | 31 | |
| 11 | 2012 | 27 | |
| 12 | 2015 | 25 | |
| 13 | 2021 | 23 | |
| 14 | 2021 | 22 | |
| 15 | 2019 | 22 | |
| 16 | 2021 | 21 | |
| 17 | 2023 | 19 | |
| 18 | 2023 | 19 | |
| 19 | 2021 | 16 | |
| 20 | 2021 | 14 |
About Yun Li
Yun Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Media Technology and Computational Theory and Mathematics, having authored 104 papers that have together received 1.3k indexed citations. Recurring topics across this work include Topic Modeling (23 papers), Natural Language Processing Techniques (16 papers), Text and Document Classification Technologies (15 papers), Rough Sets and Fuzzy Logic (11 papers), Data Mining Algorithms and Applications (11 papers), Recommender Systems and Techniques (10 papers), Face and Expression Recognition (9 papers) and Image Enhancement Techniques (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (405 citations), Artificial Intelligence (523 citations), Media Technology (141 citations), General Social Sciences (50 citations) and Information Systems (222 citations). Yun Li has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Yunhao Yuan, Jipeng Qiang, Xindong Wu, Yujie Li, Seiichi Serikawa, Yi Zhu, Huimin Lu, Jianru Li, Zhenyu Qian and Xin Li. Their work appears in journals such as IEEE Access, Frontiers of Computer Science, Applied Intelligence, Applied Sciences 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.