Yillbyung Lee
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Artificial Intelligence
- Information Systems top 10%
- Marketing top 10%
- Co-authors
- Eunju KimWooju KimJi-Hyun ParkKang Ryoung ParkSung-Bae ChoJaihie KimYung-Cheol ByunSung-Hyuk Cha
- Topics
- Handwritten Text Recognition Techniques (7 papers)Image Retrieval and Classification Techniques (6 papers)Image Processing and 3D Reconstruction (5 papers)
- Partner nations
- South KoreaUnited States
In The Last Decade
Yillbyung Lee
22 papers receiving 253 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 100
- Signal Processing 85
- Artificial Intelligence 77
- Information Systems 62
- Marketing 48
Countries citing papers authored by Yillbyung Lee
This map shows the geographic impact of Yillbyung 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 Yillbyung Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yillbyung Lee more than expected).
Fields of papers citing papers by Yillbyung Lee
This network shows the impact of papers produced by Yillbyung 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 Yillbyung Lee. The network helps show where Yillbyung Lee may publish in the future.
Co-authorship network of co-authors of Yillbyung Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Yillbyung Lee. A scholar is included among the top collaborators of Yillbyung 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 Yillbyung Lee. Yillbyung 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 | 8 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 20 | |
| 5 | 2 | |
| 6 | DLDA-based iris recognition from image sequences with various focus information | 0 |
| 7 | 3 | |
| 8 | 19 | |
| 9 | 2 | |
| 10 | 36 | |
| 11 | 121 | |
| 12 | 1 | |
| 13 | A Saliency Map Model for Color Images using Statistical Information and Local Competitive Relations of Extracted Features | 1 |
| 14 | 0 | |
| 15 | 1 | |
| 16 | 10 | |
| 17 | 15 | |
| 18 | 1 | |
| 19 | 7 | |
| 20 | A Neural Network Model of Frog Retin: A Discrete Time-Saving Approach | 11 |
About Yillbyung Lee
Yillbyung Lee is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Signal Processing, having authored 24 papers that have together received 279 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (7 papers), Image Retrieval and Classification Techniques (6 papers) and Image Processing and 3D Reconstruction (5 papers). The work is most often cited by research in Signal Processing (85 citations), Marketing (48 citations) and Computer Vision and Pattern Recognition (100 citations). Yillbyung Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Eunju Kim, Wooju Kim, Ji-Hyun Park, Kang Ryoung Park, Sung-Bae Cho, Jaihie Kim, Yung-Cheol Byun, Sung-Hyuk Cha, Charles C. Tappert and Hyunjin Lee. Their work appears in journals such as Neural Networks, Decision Support Systems and Pattern Recognition Letters.
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.