Sang Jun Lee
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- Industrial Vision Systems and Defect Detection 13
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- Advanced Vision and Imaging 15
- Image and Object Detection Techniques 11
- Handwritten Text Recognition Techniques 8
- Optical measurement and interference techniques 8
- Video Surveillance and Tracking Methods 5
- Media Technology top 5%
- Geology top 10%
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- Robotics and Sensor-Based Localization 11
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- Surface Roughness and Optical Measurements 5
- Co-authors
- Jong Pil YunSang Woo KimGyogwon KooMin Su KimWooSang ShinChungki LeeSang M. LeeJae Wook Jeon
- Cited by
- Industrial and Manufacturing EngineeringComputer Vision and Pattern RecognitionMedia Technology
- Journals
- Scientific Reports (2 papers)Expert Systems with Applications (2 papers)IEEE Access (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Sang Jun Lee
57 papers receiving 828 citations
Peers
Comparison fields: 5 of 95
- Industrial and Manufacturing Engineering 307
- Computer Vision and Pattern Recognition 359
- Media Technology 76
- Information Systems and Management 56
- Geology 34
Countries citing papers authored by Sang Jun Lee
This map shows the geographic impact of Sang 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 Sang 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 Sang Jun Lee more than expected).
Fields of papers citing papers by Sang Jun Lee
This network shows the impact of papers produced by Sang 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 Sang Jun Lee. The network helps show where Sang Jun Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sang 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 6 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 5 | |
| 11 | 2021 | 1 | |
| 12 | 2019 | 5 | |
| 13 | 2019 | 7 | |
| 14 | 2017 | 6 | |
| 15 | 2016 | 52 | |
| 16 | 2015 | 1 | |
| 17 | FPGA design and implementation of a real-time vehicle detection system | 2012 | 1 |
| 18 | Hardware architecture for detecting laser point using FPGA | 2012 | 2 |
| 19 | 2007 | 5 | |
| 20 | 2005 | 60 |
About Sang Jun Lee
Sang Jun Lee is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Media Technology, having authored 60 papers that have together received 846 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (15 papers), Industrial Vision Systems and Defect Detection (13 papers), Image and Object Detection Techniques (11 papers), Robotics and Sensor-Based Localization (11 papers), Handwritten Text Recognition Techniques (8 papers), Optical measurement and interference techniques (8 papers), Surface Roughness and Optical Measurements (5 papers) and Video Surveillance and Tracking Methods (5 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (307 citations), Computer Vision and Pattern Recognition (359 citations) and Media Technology (76 citations). Sang Jun Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Jong Pil Yun, Sang Woo Kim, Gyogwon Koo, Min Su Kim, WooSang Shin, Chungki Lee, Sang M. Lee, Jae Wook Jeon, Vinh Dinh Nguyen and Yong-Ju Jeon. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.