Seonguk Seo
About
In The Last Decade
Seonguk Seo
11 papers receiving 395 citations
Peers
Comparison fields: 5 of 66
- Computer Vision and Pattern Recognition 237
- Artificial Intelligence 187
- Computational Mechanics 49
- Computer Graphics and Computer-Aided Design 49
- Radiology, Nuclear Medicine and Imaging 46
Countries citing papers authored by Seonguk Seo
This map shows the geographic impact of Seonguk Seo'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 Seonguk Seo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seonguk Seo more than expected).
Fields of papers citing papers by Seonguk Seo
This network shows the impact of papers produced by Seonguk Seo. 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 Seonguk Seo. The network helps show where Seonguk Seo may publish in the future.
Co-authorship network of co-authors of Seonguk Seo
This figure shows the co-authorship network connecting the top 25 collaborators of Seonguk Seo. A scholar is included among the top collaborators of Seonguk Seo 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 Seonguk Seo. Seonguk Seo 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 | 0 | |
| 3 | 12 | |
| 4 | 86 | |
| 5 | 1 | |
| 6 | 13 | |
| 7 | 7 | |
| 8 | Learning to Optimize Domain Specific Normalization with Domain Augmentation for Domain Generalization | 1 |
| 9 | 249 | |
| 10 | Confidence Calibration in Deep Neural Networks through Stochastic Inferences | 1 |
| 11 | 26 | |
| 12 | 5 | |
| 13 | 6 |
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.