Youngkwan Cho

429 total citations
14 papers, 272 citations indexed

About

Youngkwan Cho is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Youngkwan Cho has authored 14 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 5 papers in Aerospace Engineering and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Youngkwan Cho's work include Augmented Reality Applications (7 papers), Robotics and Sensor-Based Localization (5 papers) and Neural dynamics and brain function (4 papers). Youngkwan Cho is often cited by papers focused on Augmented Reality Applications (7 papers), Robotics and Sensor-Based Localization (5 papers) and Neural dynamics and brain function (4 papers). Youngkwan Cho collaborates with scholars based in United States and South Korea. Youngkwan Cho's co-authors include Ulrich Neumann, Narayan Srinivasa, Mike Daily, David W. Payton, N. Srinivasa, Jong Weon Lee, Corey M. Thibeault, Jose Cruz-Albrecht, Jae Hong Seo and Ji Young Kim and has published in prestigious journals such as Cancer Research, IEEE Transactions on Neural Networks and Learning Systems and Computer Vision and Image Understanding.

In The Last Decade

Youngkwan Cho

14 papers receiving 245 citations

Peers

Youngkwan Cho
Leo Miyashita Japan
Olaf Booij Netherlands
David Weikersdorfer Germany
V. Sundareswaran United States
Bernd Michaelis Germany
Kyhyun Um South Korea
Xavier Clady France
Daniele De Gregorio Italy
Antonio Zea Germany
Chethan M. Parameshwara United States
Leo Miyashita Japan
Youngkwan Cho
Citations per year, relative to Youngkwan Cho Youngkwan Cho (= 1×) peers Leo Miyashita

Countries citing papers authored by Youngkwan Cho

Since Specialization
Citations

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

Fields of papers citing papers by Youngkwan Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Youngkwan 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 Youngkwan Cho. The network helps show where Youngkwan Cho may publish in the future.

Co-authorship network of co-authors of Youngkwan Cho

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

All Works

14 of 14 papers shown
1.
Cho, Youngkwan, et al.. (2025). MF-LPR 2 : Multi-frame license plate image restoration and recognition using optical flow. Computer Vision and Image Understanding. 256. 104361–104361. 1 indexed citations
2.
Oh, Eunhye, et al.. (2017). Abstract 5463: Disulfiram suppresses metastasis via induction of anoikis and calpain activation in triple-negative breast cancer. Cancer Research. 77(13_Supplement). 5463–5463. 1 indexed citations
3.
Thibeault, Corey M., et al.. (2014). HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters. IEEE Transactions on Neural Networks and Learning Systems. 25(2). 316–331. 44 indexed citations
4.
Srinivasa, Narayan & Youngkwan Cho. (2014). Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity. Frontiers in Computational Neuroscience. 8. 159–159. 12 indexed citations
5.
Srinivasa, N. & Youngkwan Cho. (2012). Self-Organizing Spiking Neural Model for Learning Fault-Tolerant Spatio-Motor Transformations. IEEE Transactions on Neural Networks and Learning Systems. 23(10). 1526–1538. 14 indexed citations
6.
Srinivasa, N., et al.. (2012). Programming Time-Multiplexed Reconfigurable Hardware Using a Scalable Neuromorphic Compiler. IEEE Transactions on Neural Networks and Learning Systems. 23(6). 889–901. 14 indexed citations
7.
Daily, Mike, et al.. (2003). World embedded interfaces for human-robot interaction. 6 pp.–6 pp.. 42 indexed citations
8.
Cho, Youngkwan & Ulrich Neumann. (2002). Multi-ring color fiducial systems for scalable fiducial tracking augmented reality. 212–212. 21 indexed citations
9.
10.
Cho, Youngkwan, et al.. (2002). Improved specular highlights with adaptive shading. 20. 38–46. 5 indexed citations
11.
Cho, Youngkwan & Ulrich Neumann. (2001). Multiring Fiducial Systems for Scalable Fiducial-Tracking Augmented Reality. PRESENCE Virtual and Augmented Reality. 10(6). 599–612. 9 indexed citations
12.
Neumann, Ulrich & Youngkwan Cho. (1999). Scalable fiducial-tracking augmented reality. 136–136. 4 indexed citations
13.
Cho, Youngkwan, Jong Weon Lee, & Ulrich Neumann. (1999). A multi-ring fiducial system and an intensity-invariant detection method for scalable augmented reality. 147–165. 25 indexed citations
14.
Neumann, Ulrich & Youngkwan Cho. (1996). A self-tracking augmented reality system. 109–115. 67 indexed citations

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