Junsuk Choe
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 0.5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Media Technology top 1%
- Industrial and Manufacturing Engineering top 2%
- Co-authors
- Sangdoo YunSeong Joon OhDongyoon HanSanghyuk ChunYoungjoon YooHyunjung ShimSeungho LeeEunji Kim
- Topics
- Domain Adaptation and Few-Shot Learning (14 papers)Advanced Neural Network Applications (13 papers)Advanced Image and Video Retrieval Techniques (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern RecognitionInformation Sciences
- Partner nations
- South KoreaGermanyUnited States
In The Last Decade
Junsuk Choe
21 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Computer Vision and Pattern Recognition 2.1k
- Artificial Intelligence 1.6k
- Radiology, Nuclear Medicine and Imaging 305
- Media Technology 284
- Industrial and Manufacturing Engineering 188
Countries citing papers authored by Junsuk Choe
This map shows the geographic impact of Junsuk Choe'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 Junsuk Choe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junsuk Choe more than expected).
Fields of papers citing papers by Junsuk Choe
This network shows the impact of papers produced by Junsuk Choe. 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 Junsuk Choe. The network helps show where Junsuk Choe may publish in the future.
Co-authorship network of co-authors of Junsuk Choe
This figure shows the co-authorship network connecting the top 25 collaborators of Junsuk Choe. A scholar is included among the top collaborators of Junsuk Choe 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 Junsuk Choe. Junsuk Choe 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 11 | |
| 10 | 2 | |
| 11 | 17 | |
| 12 | 18 | |
| 13 | 78 | |
| 14 | CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Featuresbreakdown → | 2641 |
| 15 | 1 | |
| 16 | 40 | |
| 17 | 1 | |
| 18 | 15 | |
| 19 | 1 | |
| 20 | 19 |
About Junsuk Choe
Junsuk Choe is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 25 papers that have together received 3.2k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (14 papers), Advanced Neural Network Applications (13 papers) and Advanced Image and Video Retrieval Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Artificial Intelligence (1.6k citations) and Media Technology (284 citations). Junsuk Choe has collaborated with scholars based in South Korea, Germany and United States. Frequent co-authors include Sangdoo Yun, Seong Joon Oh, Dongyoon Han, Sanghyuk Chun, Youngjoon Yoo, Hyunjung Shim, Seungho Lee, Eunji Kim, Sungroh Yoon and Jungbeom Lee. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition 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.