Seung‐Hwan Bae
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Aerospace Engineering top 10%
- Electrical and Electronic Engineering
- Safety, Risk, Reliability and Quality top 5%
- Co-authors
- Kuk‐Jin YoonYongsang YooHyun KimHyuk‐Jae LeeJongyoul ParkPaul CoddingtonDu Yong KimJu Hong Yoon
- Topics
- Advanced Neural Network Applications (10 papers)Video Surveillance and Tracking Methods (8 papers)Advanced Image and Video Retrieval Techniques (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionSafety, Risk, Reliability and QualityArtificial Intelligence
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Access
- Partner nations
- South KoreaUnited States
In The Last Decade
Seung‐Hwan Bae
26 papers receiving 771 citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 647
- Artificial Intelligence 211
- Aerospace Engineering 139
- Electrical and Electronic Engineering 94
- Safety, Risk, Reliability and Quality 92
Countries citing papers authored by Seung‐Hwan Bae
This map shows the geographic impact of Seung‐Hwan Bae'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 Seung‐Hwan Bae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seung‐Hwan Bae more than expected).
Fields of papers citing papers by Seung‐Hwan Bae
This network shows the impact of papers produced by Seung‐Hwan Bae. 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 Seung‐Hwan Bae. The network helps show where Seung‐Hwan Bae may publish in the future.
Co-authorship network of co-authors of Seung‐Hwan Bae
This figure shows the co-authorship network connecting the top 25 collaborators of Seung‐Hwan Bae. A scholar is included among the top collaborators of Seung‐Hwan Bae 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 Seung‐Hwan Bae. Seung‐Hwan Bae 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 | 7 | |
| 5 | 3 | |
| 6 | 16 | |
| 7 | 5 | |
| 8 | 5 | |
| 9 | 4 | |
| 10 | 13 | |
| 11 | 25 | |
| 12 | 22 | |
| 13 | 6 | |
| 14 | 29 | |
| 15 | 6 | |
| 16 | 5 | |
| 17 | 78 | |
| 18 | 32 | |
| 19 | 281 | |
| 20 | 6 |
About Seung‐Hwan Bae
Seung‐Hwan Bae is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Hardware and Architecture, having authored 28 papers that have together received 788 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (10 papers), Video Surveillance and Tracking Methods (8 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (647 citations), Safety, Risk, Reliability and Quality (92 citations) and Artificial Intelligence (211 citations). Seung‐Hwan Bae has collaborated with scholars based in South Korea and United States. Frequent co-authors include Kuk‐Jin Yoon, Yongsang Yoo, Hyun Kim, Hyuk‐Jae Lee, Jongyoul Park, Paul Coddington, Du Yong Kim, Ju Hong Yoon, Vladimir Shin and Hoon Sung Chwa. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing 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.