Kyungdon Joo
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 5%
- Geology top 5%
- Media Technology top 5%
- Electrical and Electronic Engineering
- Co-authors
- In So KweonTae-Hyun OhHyowon HaFrançois RameauJean‐Charles BazinKibaek ParkPyojin KimNam Il Kim
- Topics
- Advanced Vision and Imaging (23 papers)Robotics and Sensor-Based Localization (19 papers)Optical measurement and interference techniques (12 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionPattern Recognition Letters
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Kyungdon Joo
34 papers receiving 462 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 352
- Aerospace Engineering 241
- Geology 85
- Media Technology 58
- Electrical and Electronic Engineering 47
Countries citing papers authored by Kyungdon Joo
This map shows the geographic impact of Kyungdon Joo'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 Kyungdon Joo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyungdon Joo more than expected).
Fields of papers citing papers by Kyungdon Joo
This network shows the impact of papers produced by Kyungdon Joo. 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 Kyungdon Joo. The network helps show where Kyungdon Joo may publish in the future.
Co-authorship network of co-authors of Kyungdon Joo
This figure shows the co-authorship network connecting the top 25 collaborators of Kyungdon Joo. A scholar is included among the top collaborators of Kyungdon Joo 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 Kyungdon Joo. Kyungdon Joo 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 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 11 | |
| 10 | 3 | |
| 11 | 2 | |
| 12 | 12 | |
| 13 | 2 | |
| 14 | 6 | |
| 15 | 15 | |
| 16 | 27 | |
| 17 | 6 | |
| 18 | 22 | |
| 19 | 39 | |
| 20 | 1 |
About Kyungdon Joo
Kyungdon Joo is a scholar working on Computer Vision and Pattern Recognition, Geology and Aerospace Engineering, having authored 37 papers that have together received 470 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (23 papers), Robotics and Sensor-Based Localization (19 papers) and Optical measurement and interference techniques (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (352 citations), Geology (85 citations) and Aerospace Engineering (241 citations). Kyungdon Joo has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include In So Kweon, Tae-Hyun Oh, Hyowon Ha, François Rameau, Jean‐Charles Bazin, Kibaek Park, Pyojin Kim, Nam Il Kim, Jinsoo Choi and Hae‐Gon Jeon. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision 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.