Jaesik Min
- Computer Vision and Pattern Recognition top 0.5%
- Signal Processing top 1%
- Artificial Intelligence top 10%
- Computational Mechanics top 5%
- Media Technology top 5%
- Co-authors
- Kevin W. BowyerPatrick J. FlynnJeffrey Wen Wei ChangKari L. HoffmanJorge S. MarquesThomas E. ScruggsWilliam J. WorekP. Jonathon Phillips
- Topics
- Robotics and Sensor-Based Localization (5 papers)Image and Object Detection Techniques (3 papers)Advanced Vision and Imaging (2 papers)
- Journals
- IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)Computer Vision and Image Understanding2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United StatesSouth KoreaChina
In The Last Decade
Jaesik Min
8 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Computer Vision and Pattern Recognition 1.7k
- Signal Processing 697
- Artificial Intelligence 190
- Computational Mechanics 172
- Media Technology 132
Countries citing papers authored by Jaesik Min
This map shows the geographic impact of Jaesik Min'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 Jaesik Min with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaesik Min more than expected).
Fields of papers citing papers by Jaesik Min
This network shows the impact of papers produced by Jaesik Min. 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 Jaesik Min. The network helps show where Jaesik Min may publish in the future.
Co-authorship network of co-authors of Jaesik Min
This figure shows the co-authorship network connecting the top 25 collaborators of Jaesik Min. A scholar is included among the top collaborators of Jaesik Min 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 Jaesik Min. Jaesik Min is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 92 | |
| 2 | 1 | |
| 3 | 18 | |
| 4 | Overview of the Face Recognition Grand Challengebreakdown → | 1678 |
| 5 | 41 | |
| 6 | 9 | |
| 7 | 8 | |
| 8 | 9 | |
| 9 | Improvement of range image segmentation by utilizing a performance evaluation framework | 1 |
About Jaesik Min
Jaesik Min is a scholar working on Computer Vision and Pattern Recognition, Instrumentation and Media Technology, having authored 9 papers that have together received 1.9k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (5 papers), Image and Object Detection Techniques (3 papers) and Advanced Vision and Imaging (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Signal Processing (697 citations) and Media Technology (132 citations). Jaesik Min has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Kevin W. Bowyer, Patrick J. Flynn, Jeffrey Wen Wei Chang, Kari L. Hoffman, Jorge S. Marques, Thomas E. Scruggs, William J. Worek, P. Jonathon Phillips, Mark Powell and Sungyong Baik. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Computer Vision and Image Understanding and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.