Jaejun Lee

495 citations
22 papers · 233 · h-index 6

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Domain Adaptation and Few-Shot Learning
    • Speech Recognition and Synthesis
    • Advanced Graph Neural Networks
    • Machine Learning and Data Classification
    • Multimodal Machine Learning Applications
    • Advanced Neural Network Applications

Papers in

Jaejun Lee

19 papers receiving 222 citations

Peers

Jaejun Lee
Comparison fields: 5 of 48
  • Artificial Intelligence 175
  • Computer Vision and Pattern Recognition 86
  • Computational Mathematics 1
  • Health Informatics 2
  • Signal Processing 15
Replace Ji Xin with:
Ji Xin Canada
Tinglin Huang United States
Jiayan Qiu Australia
Anirudh Ravula United States
Rama Kumar Pasumarthi United States
Xuwu Wang China
Giulio Zhou United States
Jipeng Zhang China
Chengtai Cao China
Jaejun Lee relative to Ji Xin Canada Ji Xin's profile →
Citations per field
00.5×1.5×
Ji Xin · 1×
Citations per year

Countries citing papers authored by Jaejun Lee

Since Specialization
Citations

This map shows the geographic impact of Jaejun 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 Jaejun Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaejun Lee more than expected).

Fields of papers citing papers by Jaejun Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jaejun 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 Jaejun Lee. The network helps show where Jaejun Lee may publish in the future.

Co-authors

The 25 scholars most cited alongside Jaejun Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jaejun Lee Line = papers co-authored together Jaejun Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020167
2 202212
3 202010
4 20238
5 20236
6 20205
7 20213
8 20193
9 20053
10 20183
11 20242
12
A Study on the Traffic Information System Development Using DSRC
20092
13 20202
14 20251
15 20161
16 20141
17 20161
18 20241
19 20211
20 20201

About Jaejun Lee

Jaejun Lee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Control and Systems Engineering and Information Systems, having authored 22 papers that have together received 233 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Multimodal Machine Learning Applications (3 papers), Speech Recognition and Synthesis (3 papers), Speech and dialogue systems (2 papers), Advanced Graph Neural Networks (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Speech and Audio Processing (2 papers) and Face recognition and analysis (2 papers). The work is most often cited by research in Artificial Intelligence (175 citations), Computer Vision and Pattern Recognition (86 citations), Computational Mathematics (1 citation), Health Informatics (2 citations) and Signal Processing (15 citations). Jaejun Lee has collaborated with scholars based in South Korea, Canada and United States. Frequent co-authors include Jimmy Lin, Raphael Tang, Ji Xin, Yaoliang Yu, Joyce Jiyoung Whang, Sungho Jo, Heetae Cho, Sungwon Kang, Jee-Hwan Ryu and Jofish Kaye. Their work appears in journals such as Applied Sciences, IEEE Robotics and Automation Letters, Knee Surgery and Related Research, Journal of Institute of Control Robotics and Systems and The Journal of The Korea Institute of Intelligent Transport Systems.

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.

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