Min-Cheol Hong
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Signal Processing top 10%
- Artificial Intelligence
- Computer Networks and Communications
- Co-authors
- Aggelos K. KatsaggelosMoon Gi KangTuan-Anh NguyenSeongsoo LeeLisimachos P. KondiBeomsu KimMyoung‐Jin KimKihwan Kim
- Topics
- Image and Signal Denoising Methods (21 papers)Advanced Image Processing Techniques (21 papers)Advanced Vision and Imaging (18 papers)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Min-Cheol Hong
37 papers receiving 254 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 242
- Media Technology 87
- Signal Processing 76
- Artificial Intelligence 17
- Computer Networks and Communications 16
Countries citing papers authored by Min-Cheol Hong
This map shows the geographic impact of Min-Cheol Hong'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 Min-Cheol Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min-Cheol Hong more than expected).
Fields of papers citing papers by Min-Cheol Hong
This network shows the impact of papers produced by Min-Cheol Hong. 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 Min-Cheol Hong. The network helps show where Min-Cheol Hong may publish in the future.
Co-authorship network of co-authors of Min-Cheol Hong
This figure shows the co-authorship network connecting the top 25 collaborators of Min-Cheol Hong. A scholar is included among the top collaborators of Min-Cheol Hong 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 Min-Cheol Hong. Min-Cheol Hong 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 | 3 | |
| 3 | 6 | |
| 4 | 7 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | An Adaptive Noise Removal Method Using Local Statistics and Generalized Gaussian Filter | 0 |
| 10 | Fast multiple reference frame selection method using inter-mode correlation | 0 |
| 11 | Spatially adaptive gradient-projection algorithm to remove blocking artifacts of H.264 video coding standard | 1 |
| 12 | 2 | |
| 13 | A Spatially Adaptive Gradient-Projection Image Restoration | 1 |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 5 | |
| 17 | 40 | |
| 18 | 2 | |
| 19 | 11 | |
| 20 | 1 |
About Min-Cheol Hong
Min-Cheol Hong is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 50 papers that have together received 278 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (21 papers), Advanced Image Processing Techniques (21 papers) and Advanced Vision and Imaging (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (242 citations), Media Technology (87 citations) and Signal Processing (76 citations). Min-Cheol Hong has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Aggelos K. Katsaggelos, Moon Gi Kang, Tuan-Anh Nguyen, Seongsoo Lee, Lisimachos P. Kondi, Beomsu Kim, Myoung‐Jin Kim, Kihwan Kim, Young Jin Jeon and J.C. Brailean. Their work appears in journals such as IEEE Access, Sensors and IEEE Transactions on Multimedia.
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.