Seong Jae Hwang
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Cognitive Neuroscience
- Computational Mechanics
- Co-authors
- Hyunwoo J. KimVikas SinghMaxwell D. CollinsDana TudorascuDavneet MinhasSanghyeok LeeNagesh AdluruSterling C. Johnson
- Topics
- Advanced Neuroimaging Techniques and Applications (9 papers)Functional Brain Connectivity Studies (8 papers)Domain Adaptation and Few-Shot Learning (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingComputer Graphics and Computer-Aided Design
- Journals
- PLoS ONENeuroImageScientific Reports
- Partner nations
- United StatesSouth KoreaSweden
In The Last Decade
Seong Jae Hwang
26 papers receiving 294 citations
Peers
Comparison fields: 5 of 91
- Computer Vision and Pattern Recognition 98
- Artificial Intelligence 86
- Radiology, Nuclear Medicine and Imaging 73
- Cognitive Neuroscience 39
- Computational Mechanics 25
Countries citing papers authored by Seong Jae Hwang
This map shows the geographic impact of Seong Jae Hwang'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 Seong Jae Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seong Jae Hwang more than expected).
Fields of papers citing papers by Seong Jae Hwang
This network shows the impact of papers produced by Seong Jae Hwang. 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 Seong Jae Hwang. The network helps show where Seong Jae Hwang may publish in the future.
Co-authorship network of co-authors of Seong Jae Hwang
This figure shows the co-authorship network connecting the top 25 collaborators of Seong Jae Hwang. A scholar is included among the top collaborators of Seong Jae Hwang 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 Seong Jae Hwang. Seong Jae Hwang 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 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 46 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 14 | |
| 11 | Cycle Consistent Embedding of 3D Brains with Auto-Encoding Generative Adversarial Networks | 2 |
| 12 | 8 | |
| 13 | 33 | |
| 14 | 13 | |
| 15 | 1 | |
| 16 | 9 | |
| 17 | 21 | |
| 18 | 2 | |
| 19 | 7 | |
| 20 | 6 |
About Seong Jae Hwang
Seong Jae Hwang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 33 papers that have together received 303 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (9 papers), Functional Brain Connectivity Studies (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (98 citations), Radiology, Nuclear Medicine and Imaging (73 citations) and Computer Graphics and Computer-Aided Design (10 citations). Seong Jae Hwang has collaborated with scholars based in United States, South Korea and Sweden. Frequent co-authors include Hyunwoo J. Kim, Vikas Singh, Maxwell D. Collins, Dana Tudorascu, Davneet Minhas, Sanghyeok Lee, Nagesh Adluru, Sterling C. Johnson, Jaewon Lee and Houri K. Vorperian. Their work appears in journals such as PLoS ONE, NeuroImage and Scientific Reports.
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.