Sungwoong Kim
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Biomedical Engineering
- Electrical and Electronic Engineering
- Media Technology top 5%
- Co-authors
- Chang D. YooTaesup KimJongmin KimSebastian NowozinPushmeet KohliIldoo KimAnkur SinghHochan Chang
- Topics
- Advanced Image and Video Retrieval Techniques (7 papers)Domain Adaptation and Few-Shot Learning (6 papers)Gas Sensing Nanomaterials and Sensors (4 papers)
- Journals
- Nature CommunicationsIEEE Transactions on Pattern Analysis and Machine IntelligenceScientific Reports
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Sungwoong Kim
26 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Artificial Intelligence 502
- Computer Vision and Pattern Recognition 465
- Biomedical Engineering 192
- Electrical and Electronic Engineering 89
- Media Technology 76
Countries citing papers authored by Sungwoong Kim
This map shows the geographic impact of Sungwoong Kim'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 Sungwoong Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungwoong Kim more than expected).
Fields of papers citing papers by Sungwoong Kim
This network shows the impact of papers produced by Sungwoong Kim. 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 Sungwoong Kim. The network helps show where Sungwoong Kim may publish in the future.
Co-authorship network of co-authors of Sungwoong Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Sungwoong Kim. A scholar is included among the top collaborators of Sungwoong Kim 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 Sungwoong Kim. Sungwoong Kim 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 | 6 | |
| 4 | 52 | |
| 5 | 2 | |
| 6 | 33 | |
| 7 | 67 | |
| 8 | 33 | |
| 9 | Fast AutoAugment | 33 |
| 10 | 1 | |
| 11 | 93 | |
| 12 | 3 | |
| 13 | 37 | |
| 14 | 77 | |
| 15 | 84 | |
| 16 | 16 | |
| 17 | Higher-Order Correlation Clustering for Image Segmentation | 71 |
| 18 | 4 | |
| 19 | 1 | |
| 20 | 22 |
About Sungwoong Kim
Sungwoong Kim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 27 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (7 papers), Domain Adaptation and Few-Shot Learning (6 papers) and Gas Sensing Nanomaterials and Sensors (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (465 citations), Artificial Intelligence (502 citations) and Media Technology (76 citations). Sungwoong Kim has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Chang D. Yoo, Taesup Kim, Jongmin Kim, Sebastian Nowozin, Pushmeet Kohli, Ildoo Kim, Ankur Singh, Hochan Chang, Seungwoo Lee and Hyunjung Yi. Their work appears in journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence 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.