Jun Lee
Impact in
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- Advanced Clustering Algorithms Research
- Human-Computer Interaction top 10%
Papers in ⓘ
-
- Network Security and Intrusion Detection 6
-
- Augmented Reality Applications 7
- Co-authors
- Lian Duan (2 shared papers)Lida Xu (2 shared papers)Ying Liu (1 shared paper)Feng Guo (1 shared paper)Takaki Komiyama (1 shared paper)Andrew J. Peters (1 shared paper)Nathan G. Hedrick (1 shared paper)Hyun Kwon (5 shared papers)
- Journals
- IEEE Access (3 papers)Sustainability (3 papers)Japanese Journal of Applied Physics (2 papers)Ceramics International (1 paper)IEEE Transactions on Consumer Electronics (1 paper)
- Partner nations
- South KoreaJapanUnited States
In The Last Decade
Jun Lee
71 papers receiving 748 citations
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 277
- Human-Computer Interaction 46
- Signal Processing 83
- Transportation 45
- Computer Networks and Communications 138
Countries citing papers authored by Jun Lee
This map shows the geographic impact of Jun Lee'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 Jun Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Lee more than expected).
Fields of papers citing papers by Jun Lee
This network shows the impact of papers produced by Jun Lee. 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 Jun Lee. The network helps show where Jun Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Lee, 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 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 187 | |
| 2 | 2008 | 149 | |
| 3 | 2017 | 99 | |
| 4 | 2007 | 70 | |
| 5 | 2017 | 18 | |
| 6 | 2014 | 18 | |
| 7 | 2021 | 15 | |
| 8 | 2020 | 14 | |
| 9 | 2007 | 13 | |
| 10 | 2021 | 13 | |
| 11 | 2006 | 12 | |
| 12 | 2023 | 9 | |
| 13 | 2011 | 9 | |
| 14 | 2019 | 8 | |
| 15 | 2020 | 8 | |
| 16 | 2012 | 7 | |
| 17 | 2012 | 6 | |
| 18 | 2021 | 6 | |
| 19 | 2004 | 5 | |
| 20 | 2012 | 5 |
About Jun Lee
Jun Lee is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction and Transportation, having authored 90 papers that have together received 784 indexed citations. Recurring topics across this work include Interactive and Immersive Displays (8 papers), Human Mobility and Location-Based Analysis (8 papers), Augmented Reality Applications (7 papers), Virtual Reality Applications and Impacts (6 papers), 3D Modeling in Geospatial Applications (6 papers), Tactile and Sensory Interactions (6 papers), Multimedia Communication and Technology (6 papers) and Network Security and Intrusion Detection (6 papers). The work is most often cited by research in Artificial Intelligence (277 citations), Human-Computer Interaction (46 citations), Signal Processing (83 citations), Transportation (45 citations) and Computer Networks and Communications (138 citations). Jun Lee has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Lian Duan, Lida Xu, Ying Liu, Feng Guo, Takaki Komiyama, Andrew J. Peters, Nathan G. Hedrick, Hyun Kwon, Hae Jin Hwang and Jee‐In Kim. Their work appears in journals such as IEEE Access, Sustainability, Japanese Journal of Applied Physics, Ceramics International and IEEE Transactions on Consumer Electronics.
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.