MyeongAh Cho
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Biomedical Engineering
- Signal Processing
- Co-authors
- Sangyoun LeeTaeoh KimSuhwan ChoMinjung KimChaewon ParkIg-Jae KimTae‐Young ChungTaeyoung Chung
- Topics
- Anomaly Detection Techniques and Applications (6 papers)Video Surveillance and Tracking Methods (5 papers)Face recognition and analysis (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Networks and Communications
- Journals
- IEEE AccessPattern RecognitionIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- South KoreaPoland
In The Last Decade
MyeongAh Cho
16 papers receiving 255 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 158
- Computer Vision and Pattern Recognition 150
- Computer Networks and Communications 108
- Biomedical Engineering 68
- Signal Processing 28
Countries citing papers authored by MyeongAh Cho
This map shows the geographic impact of MyeongAh Cho'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 MyeongAh Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites MyeongAh Cho more than expected).
Fields of papers citing papers by MyeongAh Cho
This network shows the impact of papers produced by MyeongAh Cho. 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 MyeongAh Cho. The network helps show where MyeongAh Cho may publish in the future.
Co-authorship network of co-authors of MyeongAh Cho
This figure shows the co-authorship network connecting the top 25 collaborators of MyeongAh Cho. A scholar is included among the top collaborators of MyeongAh Cho 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 MyeongAh Cho. MyeongAh Cho 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 | 8 | |
| 3 | 1 | |
| 4 | 20 | |
| 5 | 34 | |
| 6 | 3 | |
| 7 | 71 | |
| 8 | 36 | |
| 9 | 17 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | 4 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 36 | |
| 16 | 6 | |
| 17 | 5 |
About MyeongAh Cho
MyeongAh Cho is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 17 papers that have together received 260 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Video Surveillance and Tracking Methods (5 papers) and Face recognition and analysis (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (150 citations), Artificial Intelligence (158 citations) and Computer Networks and Communications (108 citations). MyeongAh Cho has collaborated with scholars based in South Korea and Poland. Frequent co-authors include Sangyoun Lee, Taeoh Kim, Suhwan Cho, Minjung Kim, Chaewon Park, Ig-Jae Kim, Minjung Kim, Tae‐Young Chung, Taeyoung Chung and Sangwon Hwang. Their work appears in journals such as IEEE Access, Pattern Recognition and IEEE Transactions on Circuits and Systems for Video Technology.
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.