Dong‐Joong Kang

1.2k total citations
70 papers, 904 citations indexed

About

Dong‐Joong Kang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Industrial and Manufacturing Engineering. According to data from OpenAlex, Dong‐Joong Kang has authored 70 papers receiving a total of 904 indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 18 papers in Media Technology and 13 papers in Industrial and Manufacturing Engineering. Recurrent topics in Dong‐Joong Kang's work include Video Surveillance and Tracking Methods (14 papers), Industrial Vision Systems and Defect Detection (12 papers) and Image and Object Detection Techniques (11 papers). Dong‐Joong Kang is often cited by papers focused on Video Surveillance and Tracking Methods (14 papers), Industrial Vision Systems and Defect Detection (12 papers) and Image and Object Detection Techniques (11 papers). Dong‐Joong Kang collaborates with scholars based in South Korea, China and United Kingdom. Dong‐Joong Kang's co-authors include Jun-Hyub Park, Teng Zhu, Jong‐Seob Won, Jeonghyun Kim, Feifei Chen, Jeonghyun Kim, Hak‐Joo Lee, Son‐Cheol Yu, Baopeng Zhang and Jin Young Kim and has published in prestigious journals such as IEEE Access, Pattern Recognition and Journal of Physics D Applied Physics.

In The Last Decade

Dong‐Joong Kang

64 papers receiving 862 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dong‐Joong Kang South Korea 17 458 283 158 142 141 70 904
Gyogwon Koo South Korea 13 181 0.4× 189 0.7× 144 0.9× 101 0.7× 57 0.4× 35 769
Huei‐Yung Lin Taiwan 20 930 2.0× 78 0.3× 134 0.8× 196 1.4× 213 1.5× 168 1.5k
Jason S. Ku United States 10 1.3k 2.7× 121 0.4× 149 0.9× 291 2.0× 75 0.5× 26 1.7k
Xinyue Zhao China 17 503 1.1× 140 0.5× 112 0.7× 37 0.3× 63 0.4× 70 785
Yuxiang Yang China 13 342 0.7× 98 0.3× 70 0.4× 62 0.4× 155 1.1× 57 884
Guifang Duan China 15 237 0.5× 236 0.8× 142 0.9× 29 0.2× 42 0.3× 71 630
Ajay Mahajan United States 18 181 0.4× 74 0.3× 225 1.4× 171 1.2× 59 0.4× 89 989
Jiaxin Chen China 17 467 1.0× 53 0.2× 355 2.2× 147 1.0× 66 0.5× 45 1.0k
Heping Chen United States 25 475 1.0× 493 1.7× 663 4.2× 154 1.1× 50 0.4× 188 2.1k
Qingnan Fan China 13 1.1k 2.3× 77 0.3× 72 0.5× 125 0.9× 415 2.9× 25 1.4k

Countries citing papers authored by Dong‐Joong Kang

Since Specialization
Citations

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

Fields of papers citing papers by Dong‐Joong Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong‐Joong Kang. 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 Dong‐Joong Kang. The network helps show where Dong‐Joong Kang may publish in the future.

Co-authorship network of co-authors of Dong‐Joong Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Dong‐Joong Kang. A scholar is included among the top collaborators of Dong‐Joong Kang 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 Dong‐Joong Kang. Dong‐Joong Kang 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
1.
Kang, Dong‐Joong, et al.. (2024). Novel method of performance-optimized metastructure design for electromagnetic wave absorption in specific band using deep learning. Engineering Applications of Artificial Intelligence. 137. 109274–109274. 2 indexed citations
2.
3.
Kang, Dong‐Joong, et al.. (2021). A new License Plate Detection and Recognition Model Based on Attention Method. 2021 21st International Conference on Control, Automation and Systems (ICCAS). 2191–2193. 1 indexed citations
4.
Kang, Dong‐Joong, et al.. (2020). Anomaly Detection of Generative Adversarial Networks considering Quality and Distortion of Images. The Journal of the Institute of Webcasting, Internet and Telecommunication. 20(3). 171–179. 2 indexed citations
5.
Kang, Dong‐Joong, et al.. (2019). Strain measurement during tensile testing using deep learning-based digital image correlation. Measurement Science and Technology. 31(1). 15014–15014. 27 indexed citations
6.
Kim, Hyunsoo, et al.. (2018). Vibration Control of a Vehicle Active Suspension System Using a DDPG Algorithm. International Conference on Control, Automation and Systems. 4 indexed citations
7.
Kang, Minguk, et al.. (2018). Finding a High Accuracy Neural Network for the Welding Defects Classification Using Efficient Neural Architecture Search via Parameter Sharing. International Conference on Control, Automation and Systems. 1 indexed citations
8.
Kang, Dong‐Joong, et al.. (2018). Localization of Welding Defects using a Weakly Supervised Neural Network. International Conference on Control, Automation and Systems. 2 indexed citations
9.
Kang, Dong‐Joong, et al.. (2018). Unified convolutional neural network for direct facial keypoints detection. The Visual Computer. 35(11). 1615–1626. 13 indexed citations
10.
Kang, Dong‐Joong, Feifei Chen, & Jun-Hyub Park. (2014). New measurement method of Poisson’s ratio of thin films by applying digital image correlation technique. International Journal of Precision Engineering and Manufacturing. 15(5). 883–888. 9 indexed citations
11.
Won, Jong‐Seob, et al.. (2014). Lane detection and tracking based on annealed particle filter. International Journal of Control Automation and Systems. 12(6). 1303–1312. 11 indexed citations
12.
Chen, Feifei, Dong‐Joong Kang, & Jun-Hyub Park. (2013). New measurement method of Poisson's ratio of PVA hydrogels using an optical flow analysis for a digital imaging system. Measurement Science and Technology. 24(5). 55602–55602. 24 indexed citations
13.
Kang, Dong‐Joong, et al.. (2011). Fast defect detection algorithm on the variety surface with random forest using GPUs. International Conference on Control, Automation and Systems. 1136–1137. 2 indexed citations
14.
Zhu, Teng, Jeonghyun Kim, & Dong‐Joong Kang. (2011). Ellipse detection using an improved randomized Hough transformation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7870. 78700U–78700U. 1 indexed citations
15.
Yu, Son‐Cheol, et al.. (2009). Development of 3D Visual Underwater Landmark Recognition Method For AUVs. 1 indexed citations
16.
Kang, Dong‐Joong, et al.. (2008). Detection of Calibration Patterns for Camera Calibration with Irregular Lighting and Complicated Backgrounds. International Journal of Control Automation and Systems. 6(5). 746–754. 11 indexed citations
17.
Kang, Dong‐Joong, et al.. (2008). A Recognition Algorithm of Suspicious Human Behaviors using Hidden Markov Models in an Intelligent Surveillance System. Journal of Korea Multimedia Society. 11(11). 1491–1500.
18.
Kang, Dong‐Joong, et al.. (2008). A detection cell using multiple points of a rotating triangle to find local planar regions from stereo depth data. Pattern Recognition Letters. 30(5). 486–493. 4 indexed citations
19.
Kang, Dong‐Joong, et al.. (2005). Fast Stereo Matching Algorithm using Edge Projection. 제어로봇시스템학회 국제학술대회 논문집. 2389–2392. 4 indexed citations
20.
Kang, Dong‐Joong, et al.. (2005). Moving Vehicle Segmentation from Plane Constraint. 제어로봇시스템학회 국제학술대회 논문집. 2393–2396. 4 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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