Heeyoul Choi
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Economics and Econometrics top 10%
- Signal Processing top 10%
- Co-authors
- Seungjin ChoiWoosung KimHeegon KimJames Won‐Ki HongHoshik LeeStanislav LangeTaesup MoonDo‐Young Lee
- Topics
- Neural Networks and Applications (15 papers)Software-Defined Networks and 5G (10 papers)Network Security and Intrusion Detection (10 papers)
- Partner nations
- South KoreaUnited StatesNorway
In The Last Decade
Heeyoul Choi
43 papers receiving 648 citations
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 201
- Computer Vision and Pattern Recognition 170
- Computer Networks and Communications 140
- Economics and Econometrics 90
- Signal Processing 82
Countries citing papers authored by Heeyoul Choi
This map shows the geographic impact of Heeyoul Choi'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 Heeyoul Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heeyoul Choi more than expected).
Fields of papers citing papers by Heeyoul Choi
This network shows the impact of papers produced by Heeyoul Choi. 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 Heeyoul Choi. The network helps show where Heeyoul Choi may publish in the future.
Co-authorship network of co-authors of Heeyoul Choi
This figure shows the co-authorship network connecting the top 25 collaborators of Heeyoul Choi. A scholar is included among the top collaborators of Heeyoul Choi 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 Heeyoul Choi. Heeyoul Choi 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 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 19 | |
| 11 | 43 | |
| 12 | 54 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 28 | |
| 16 | From Data Streams to Information Flow: Information Exchange in Child-Parent Interaction | 6 |
| 17 | 4 | |
| 18 | Sketch recognition based on manifold learning | 1 |
| 19 | Manifold integration with Markov random walks | 3 |
| 20 | 6 |
About Heeyoul Choi
Heeyoul Choi is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 681 indexed citations. Recurring topics across this work include Neural Networks and Applications (15 papers), Software-Defined Networks and 5G (10 papers) and Network Security and Intrusion Detection (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (170 citations), Signal Processing (82 citations) and Artificial Intelligence (201 citations). Heeyoul Choi has collaborated with scholars based in South Korea, United States and Norway. Frequent co-authors include Seungjin Choi, Woosung Kim, Heegon Kim, James Won‐Ki Hong, Hoshik Lee, Stanislav Lange, Taesup Moon, Do‐Young Lee, H. Kil and Sang Jun Lee. Their work appears in journals such as Journal of Geophysical Research Atmospheres, Geophysical Research Letters and Pattern Recognition.
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.