Young-Chul Yoon

436 total citations
10 papers, 227 citations indexed

About

Young-Chul Yoon is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Young-Chul Yoon has authored 10 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 4 papers in Aerospace Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Young-Chul Yoon's work include Video Surveillance and Tracking Methods (8 papers), Human Pose and Action Recognition (4 papers) and Infrared Target Detection Methodologies (4 papers). Young-Chul Yoon is often cited by papers focused on Video Surveillance and Tracking Methods (8 papers), Human Pose and Action Recognition (4 papers) and Infrared Target Detection Methodologies (4 papers). Young-Chul Yoon collaborates with scholars based in South Korea, Australia and Canada. Young-Chul Yoon's co-authors include Kwangjin Yoon, Moongu Jeon, Young-Min Song, Du Yong Kim, JiHyeon Song, Tae Sung Hwang, Kin‐Choong Yow, Jeonghwan Gwak and Kuk‐Jin Yoon and has published in prestigious journals such as IEEE Access, Sensors and Information Sciences.

In The Last Decade

Young-Chul Yoon

10 papers receiving 222 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Young-Chul Yoon South Korea 7 154 76 54 43 40 10 227
Kuan-Hui Lee United States 10 254 1.6× 26 0.3× 30 0.6× 22 0.5× 71 1.8× 15 298
Javed Pakistan 6 244 1.6× 61 0.8× 25 0.5× 14 0.3× 28 0.7× 11 308
Horesh Ben Shitrit Switzerland 6 323 2.1× 122 1.6× 9 0.2× 23 0.5× 35 0.9× 7 372
Idriss Idrissi Morocco 9 57 0.4× 130 1.7× 153 2.8× 109 2.5× 7 0.2× 13 281
Shafique United States 3 279 1.8× 64 0.8× 23 0.4× 16 0.4× 41 1.0× 4 309
Jorge García Spain 9 299 1.9× 60 0.8× 11 0.2× 14 0.3× 28 0.7× 23 354
Sara Al-Emadi Qatar 5 130 0.8× 94 1.2× 73 1.4× 68 1.6× 171 4.3× 9 330
Asad A. Butt United States 4 202 1.3× 64 0.8× 6 0.1× 10 0.2× 38 0.9× 7 222
Hajer Fradi France 11 303 2.0× 211 2.8× 29 0.5× 26 0.6× 23 0.6× 25 352
Zhiqun He China 8 300 1.9× 132 1.7× 7 0.1× 10 0.2× 52 1.3× 14 331

Countries citing papers authored by Young-Chul Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Young-Chul Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young-Chul 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 Young-Chul Yoon. The network helps show where Young-Chul Yoon may publish in the future.

Co-authorship network of co-authors of Young-Chul Yoon

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

All Works

10 of 10 papers shown
1.
Song, Young-Min, et al.. (2022). Multi-Object Tracking and Segmentation With Embedding Mask-Based Affinity Fusion in Hierarchical Data Association. IEEE Access. 10. 60643–60657. 7 indexed citations
2.
Yoon, Young-Chul, et al.. (2021). Real-Time Multi-Person Action Recognition with a Neural Compute Stick. 2021 21st International Conference on Control, Automation and Systems (ICCAS). 1135–1140. 3 indexed citations
3.
Yoon, Young-Chul, Du Yong Kim, Young-Min Song, Kwangjin Yoon, & Moongu Jeon. (2020). Online multiple pedestrians tracking using deep temporal appearance matching association. Information Sciences. 561. 326–351. 46 indexed citations
4.
Yoon, Kwangjin, Jeonghwan Gwak, Young-Min Song, Young-Chul Yoon, & Moongu Jeon. (2020). OneShotDA: Online Multi-Object Tracker With One-Shot-Learning-Based Data Association. IEEE Access. 8. 38060–38072. 26 indexed citations
5.
Song, Young-Min, Kwangjin Yoon, Young-Chul Yoon, Kin‐Choong Yow, & Moongu Jeon. (2019). Online Multi-Object Tracking With GMPHD Filter and Occlusion Group Management. IEEE Access. 7. 165103–165121. 26 indexed citations
6.
Yoon, Kwangjin, Du Yong Kim, Young-Chul Yoon, & Moongu Jeon. (2019). Data Association for Multi-Object Tracking via Deep Neural Networks. Sensors. 19(3). 559–559. 45 indexed citations
7.
Yoon, Young-Chul, et al.. (2018). Flow-based malware detection using convolutional neural network. 910–913. 52 indexed citations
8.
Yoon, Young-Chul, Young-Min Song, Kwangjin Yoon, & Moongu Jeon. (2018). Online Multi-Object Tracking Using Selective Deep Appearance Matching. 206–212. 17 indexed citations
9.
Yoon, Young-Chul & Kuk‐Jin Yoon. (2018). Animal Detection in Huge Air-view Images using CNN-based Sliding Window. 2 indexed citations
10.

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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2026