Sangho Lee
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Electrical and Electronic Engineering
- Cancer Research
- Co-authors
- Gunhee KimJangwon SuhChang‐Soo LeeByung‐Gee KimJisung KimEun‐Jung ChoHyonchol JangSung Soo Park
- Topics
- Multimodal Machine Learning Applications (4 papers)Pluripotent Stem Cells Research (3 papers)Epigenetics and DNA Methylation (3 papers)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Sangho Lee
28 papers receiving 531 citations
Peers
Comparison fields: 5 of 120
- Molecular Biology 245
- Computer Vision and Pattern Recognition 101
- Biomedical Engineering 78
- Electrical and Electronic Engineering 55
- Cancer Research 54
Countries citing papers authored by Sangho Lee
This map shows the geographic impact of Sangho Lee'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 Sangho Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sangho Lee more than expected).
Fields of papers citing papers by Sangho Lee
This network shows the impact of papers produced by Sangho Lee. 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 Sangho Lee. The network helps show where Sangho Lee may publish in the future.
Co-authorship network of co-authors of Sangho Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Sangho Lee. A scholar is included among the top collaborators of Sangho Lee 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 Sangho Lee. Sangho Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | Self-Supervised Learning of Compressed Video Representations | 8 |
| 4 | Parameter Efficient Multimodal Transformers for Video Representation Learning | 1 |
| 5 | 16 | |
| 6 | 22 | |
| 7 | 13 | |
| 8 | 16 | |
| 9 | 37 | |
| 10 | 15 | |
| 11 | 4 | |
| 12 | 129 | |
| 13 | 7 | |
| 14 | A Metabolic Pathway Drawing Algorithm for Reducing the Number of Edge Crossings | 2 |
| 15 | 4 | |
| 16 | 9 | |
| 17 | 69 | |
| 18 | 8 | |
| 19 | 31 | |
| 20 | High Temperature Cooking of Fish Protein Extracts for Plastein Reaction | 1 |
About Sangho Lee
Sangho Lee is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Signal Processing, having authored 29 papers that have together received 542 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (4 papers), Pluripotent Stem Cells Research (3 papers) and Epigenetics and DNA Methylation (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (101 citations), Cancer Research (54 citations) and Molecular Biology (245 citations). Sangho Lee has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Gunhee Kim, Jangwon Suh, Chang‐Soo Lee, Byung‐Gee Kim, Jisung Kim, Eun‐Jung Cho, Hyonchol Jang, Sung Soo Park, Yong-Kweon Kim and Hong‐Duk Youn. Their work appears in journals such as Nucleic Acids Research, Cell Metabolism and Journal of Cleaner Production.
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.