Seokju Lee
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Organic Chemistry
- Media Technology top 5%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- In So KweonFrançois RameauFei PanInkyu ShinJunsik KimJean‐Charles BazinChaoning ZhangPhilipp Benz
- Topics
- Advanced Vision and Imaging (7 papers)Robotics and Sensor-Based Localization (7 papers)Domain Adaptation and Few-Shot Learning (6 papers)
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Seokju Lee
24 papers receiving 721 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Computer Vision and Pattern Recognition 432
- Artificial Intelligence 268
- Organic Chemistry 118
- Media Technology 81
- Radiology, Nuclear Medicine and Imaging 81
Countries citing papers authored by Seokju Lee
This map shows the geographic impact of Seokju 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 Seokju Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seokju Lee more than expected).
Fields of papers citing papers by Seokju Lee
This network shows the impact of papers produced by Seokju 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 Seokju Lee. The network helps show where Seokju Lee may publish in the future.
Co-authorship network of co-authors of Seokju Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Seokju Lee. A scholar is included among the top collaborators of Seokju Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Seokju Lee. Seokju Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 99 | |
| 7 | 16 | |
| 8 | 51 | |
| 9 | 22 | |
| 10 | Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervisionbreakdown → | 248 |
| 11 | Revisiting Residual Networks with Nonlinear Shortcuts. | 13 |
| 12 | 39 | |
| 13 | 15 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 7 | |
| 17 | 2 | |
| 18 | Investigation on Water and Wastewater Treatment Techniques according to Water Environmental Change in Nakdong River Basin | 1 |
| 19 | 26 | |
| 20 | 26 |
About Seokju Lee
Seokju Lee is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence, having authored 25 papers that have together received 737 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (7 papers), Robotics and Sensor-Based Localization (7 papers) and Domain Adaptation and Few-Shot Learning (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (432 citations), Media Technology (81 citations) and Artificial Intelligence (268 citations). Seokju Lee has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include In So Kweon, François Rameau, Fei Pan, Inkyu Shin, Junsik Kim, Jean‐Charles Bazin, Chaoning Zhang, Philipp Benz, Tae-Hyun Oh and Phil Ho Lee. Their work appears in journals such as The Journal of Organic Chemistry, Organic Letters and Pattern Recognition.
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.