N.H.C. Yung

3.4k total citations · 1 hit paper
107 papers, 2.6k citations indexed

About

N.H.C. Yung is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, N.H.C. Yung has authored 107 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Computer Vision and Pattern Recognition, 25 papers in Artificial Intelligence and 17 papers in Computer Networks and Communications. Recurrent topics in N.H.C. Yung's work include Video Surveillance and Tracking Methods (25 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Advanced Vision and Imaging (15 papers). N.H.C. Yung is often cited by papers focused on Video Surveillance and Tracking Methods (25 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Advanced Vision and Imaging (15 papers). N.H.C. Yung collaborates with scholars based in Hong Kong, China and United Kingdom. N.H.C. Yung's co-authors include G.K.H. Pang, Henry Y. T. Ngan, A.H.S. Lai, Xingjian He, Clement Chun Cheong Pang, George S. K. Fung, Wan-Yi Lam, Danwei Wang, Lu Wang and Lu Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and Pattern Recognition.

In The Last Decade

N.H.C. Yung

97 papers receiving 2.4k citations

Hit Papers

Automated fabric defect d... 2011 2026 2016 2021 2011 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
N.H.C. Yung Hong Kong 25 1.7k 710 603 374 359 107 2.6k
De Xu China 32 2.2k 1.3× 1.1k 1.6× 450 0.7× 413 1.1× 72 0.2× 269 4.3k
Yanlong Cao China 24 829 0.5× 617 0.9× 415 0.7× 154 0.4× 131 0.4× 117 2.2k
Wujie Zhou China 36 3.4k 2.0× 461 0.6× 1.1k 1.8× 453 1.2× 104 0.3× 204 4.4k
Jiangmiao Pang China 15 2.5k 1.5× 227 0.3× 305 0.5× 847 2.3× 165 0.5× 31 3.2k
Ángel D. Sappa Spain 26 1.9k 1.2× 89 0.1× 512 0.8× 182 0.5× 292 0.8× 154 2.7k
Arturo de la Escalera Spain 30 2.3k 1.4× 187 0.3× 547 0.9× 377 1.0× 757 2.1× 130 3.6k
Peize Sun Hong Kong 13 1.9k 1.1× 328 0.5× 274 0.5× 688 1.8× 69 0.2× 13 2.5k
N. M. Kwok Australia 24 1.1k 0.7× 128 0.2× 233 0.4× 259 0.7× 76 0.2× 110 2.6k
Yassine Ruichek France 27 1.6k 0.9× 80 0.1× 393 0.7× 436 1.2× 248 0.7× 176 2.6k
Xizhou Zhu China 15 1.9k 1.1× 133 0.2× 249 0.4× 644 1.7× 227 0.6× 25 2.7k

Countries citing papers authored by N.H.C. Yung

Since Specialization
Citations

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

Fields of papers citing papers by N.H.C. Yung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N.H.C. Yung. 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 N.H.C. Yung. The network helps show where N.H.C. Yung may publish in the future.

Co-authorship network of co-authors of N.H.C. Yung

This figure shows the co-authorship network connecting the top 25 collaborators of N.H.C. Yung. A scholar is included among the top collaborators of N.H.C. Yung 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 N.H.C. Yung. N.H.C. Yung 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.
Ngan, Henry Y. T., et al.. (2018). Automatic incident classification for large-scale traffic data by adaptive boosting SVM. Information Sciences. 467. 59–73. 28 indexed citations
2.
Wang, Lili, Henry Y. T. Ngan, Wei Liu, & N.H.C. Yung. (2016). Anomaly Detection for Quaternion-Valued Traffic Signals. 589. 1–4. 2 indexed citations
3.
Ngan, Henry Y. T., N.H.C. Yung, & Anthony G.O. Yeh. (2015). Outlier detection in traffic data based on the Dirichlet process mixture model. IET Intelligent Transport Systems. 9(7). 773–781. 26 indexed citations
4.
Yung, N.H.C., et al.. (2015). Arm Poses Modeling for Pedestrians with Motion Prior. Journal of Signal Processing Systems. 84(2). 237–249. 1 indexed citations
5.
Yung, N.H.C., et al.. (2014). Improve scene categorization via sub-scene recognition. Machine Vision and Applications. 25(6). 1561–1572. 2 indexed citations
6.
Yung, N.H.C., et al.. (2011). A Multiple-Goal Reinforcement Learning Method for Complex Vehicle Overtaking Maneuvers. IEEE Transactions on Intelligent Transportation Systems. 12(2). 509–522. 97 indexed citations
7.
Yung, N.H.C., et al.. (2008). Scene categorization with multiscale category specific visual words. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7252. 72520N–72520N. 1 indexed citations
8.
Yung, N.H.C.. (2008). Corner detector based on global and local curvature properties. Optical Engineering. 47(5). 57008–57008. 182 indexed citations
9.
Chen, Zhuo, et al.. (2008). Pedestrian Behavior Prediction based on Motion Patterns for Vehicle-to-Pedestrian Collision Avoidance. The HKU Scholars Hub (University of Hong Kong). 316–321. 23 indexed citations
10.
Yung, N.H.C., et al.. (2007). Watershed segmentation with boundary curvature ratio based merging criterion. 7–12. 12 indexed citations
11.
Pang, Clement Chun Cheong, Wan-Yi Lam, & N.H.C. Yung. (2007). A Method for Vehicle Count in the Presence of Multiple-Vehicle Occlusions in Traffic Images. IEEE Transactions on Intelligent Transportation Systems. 8(3). 441–459. 67 indexed citations
12.
Ngan, Henry Y. T., G.K.H. Pang, & N.H.C. Yung. (2007). Motif-based defect detection for patterned fabric. Pattern Recognition. 41(6). 1878–1894. 51 indexed citations
13.
Yung, N.H.C., et al.. (2006). Performance Evaluation of Double Action Q-Learning in Moving Obstacle Avoidance Problem. The HKU Scholars Hub (University of Hong Kong). 1. 865–870. 2 indexed citations
14.
Pang, G.K.H., et al.. (2003). Fabric defect classification using wavelet frames and minimum classification error training. Conference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344). 1. 290–296. 13 indexed citations
15.
Yung, N.H.C., et al.. (2002). Adaptive search center non-linear three step search. The HKU Scholars Hub (University of Hong Kong). 2. 191–194. 2 indexed citations
16.
Yung, N.H.C., et al.. (2002). Fast and parallel video encoding by workload balancing. The HKU Scholars Hub (University of Hong Kong). 5. 4642–4647. 5 indexed citations
17.
Yung, N.H.C., et al.. (2002). Novel Neighborhood Search for Multiprocessor Scheduling with Pipelining. Journal of Parallel and Distributed Computing. 62(1). 85–110.
18.
Yung, N.H.C., et al.. (2002). Self-learning fuzzy navigation of mobile vehicle. The HKU Scholars Hub (University of Hong Kong). 2. 1465–1468. 5 indexed citations
19.
Lai, A.H.S. & N.H.C. Yung. (1998). A VIDEO-BASED SYSTEM METHODOLOGY FOR DETECTING RED LIGHT RUNNERS. 23–26. 15 indexed citations
20.
Allen, Charles R. & N.H.C. Yung. (1995). Vision assistant software : a practical introduction to image processing and pattern classifiers. Chapman & Hall eBooks. 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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