Kuk‐Jin Yoon

135 papers receiving 3.8k citations

Hit Papers

Adaptive support-weight approach for correspondence search200620262012201920062022250500750

Peers

Kuk‐Jin Yoon
Comparison fields: 5 of 124
  • Computer Vision and Pattern Recognition 3.0k
  • Electrical and Electronic Engineering 658
  • Aerospace Engineering 556
  • Artificial Intelligence 540
  • Media Technology 493
Replace Qiuping Jiang with:
Qiuping Jiang China
Zia Ur Rahman China
Xianping Fu China
Seong G. Kong South Korea
Cornelia Fermüller United States
Jiangtao Xi Australia
Ko Nishino Japan
Ming Liang China
Pingping Zhang China
Jie Qin China
Kuk‐Jin Yoon relative to Qiuping Jiang China Qiuping Jiang's profile →
Citations per field
00.5×2.9×
Qiuping Jiang · 1×
Citations per year

Countries citing papers authored by Kuk‐Jin Yoon

Since Specialization
Citations

This map shows the geographic impact of Kuk‐Jin Yoon'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 Kuk‐Jin Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuk‐Jin Yoon more than expected).

Fields of papers citing papers by Kuk‐Jin Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuk‐Jin Yoon. 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 Kuk‐Jin Yoon. The network helps show where Kuk‐Jin Yoon may publish in the future.

Co-authorship network of co-authors of Kuk‐Jin Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Kuk‐Jin Yoon. A scholar is included among the top collaborators of Kuk‐Jin Yoon 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 Kuk‐Jin Yoon. Kuk‐Jin Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
3 1
4 6
5 1
6 16
7 57
8
High Accuracy Real-Time Multi-Gas Identification by a Batch-Uniform Gas Sensor Array and Deep Learning Algorithmbreakdown →
164
9 4
10
Co-DesignMR: An MR-based Interactive Workstation Design System Supporting Collaboration
1
11 6
12 17
13 10
14 17
15 122
16 4
17 142
18
Adaptive support-weight approach for correspondence searchbreakdown →
845
19
Landmark Design and Real-Time Landmark Tracking Using Color Histogram for Mobile Robot Localization
6
20
A New Technique for Shot Detection and Key Frames Selection in Histogram Space
34

About Kuk‐Jin Yoon

Kuk‐Jin Yoon is a scholar working on Computer Vision and Pattern Recognition, Acoustics and Ultrasonics and Media Technology, having authored 143 papers that have together received 3.9k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (51 papers), Video Surveillance and Tracking Methods (29 papers) and Robotics and Sensor-Based Localization (29 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.0k citations), Media Technology (493 citations) and Computer Graphics and Computer-Aided Design (81 citations). Kuk‐Jin Yoon has collaborated with scholars based in South Korea, Canada and United States. Frequent co-authors include In So Kweon, Seung‐Hwan Bae, Lin Wang, Ju Hong Yoon, Ming–Hsuan Yang, Jaeseok Jeong, Mingu Kang, Inkyu Park, Incheol Cho and Sung-Hoon Yoon. Their work appears in journals such as ACS Nano, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

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.

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