Daniel Yeung

2.9k total citations
69 papers, 1.9k citations indexed

About

Daniel Yeung is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Daniel Yeung has authored 69 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 11 papers in Signal Processing. Recurrent topics in Daniel Yeung's work include Neural Networks and Applications (30 papers), Face and Expression Recognition (11 papers) and Machine Learning and ELM (8 papers). Daniel Yeung is often cited by papers focused on Neural Networks and Applications (30 papers), Face and Expression Recognition (11 papers) and Machine Learning and ELM (8 papers). Daniel Yeung collaborates with scholars based in Hong Kong, China and Taiwan. Daniel Yeung's co-authors include Eric C.C. Tsang, Xizhao Wang, Degang Chen, Wing W. Y. Ng, Xiaoqin Zeng, Defeng Wang, Wen‐Xiu Zhang, Suyun Zhao, Sankar K. Pal and Tharam S. Dillon and has published in prestigious journals such as Expert Systems with Applications, Pattern Recognition and Information Sciences.

In The Last Decade

Daniel Yeung

65 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Yeung Hong Kong 17 869 770 661 364 290 69 1.9k
A Bargiela United Kingdom 17 666 0.8× 924 1.2× 363 0.5× 230 0.6× 291 1.0× 56 2.1k
Dominik Ślȩzak Poland 22 999 1.1× 814 1.1× 375 0.6× 196 0.5× 743 2.6× 136 1.8k
László T. Kóczy Hungary 21 508 0.6× 1.7k 2.2× 621 0.9× 285 0.8× 165 0.6× 262 2.5k
Xin Yang China 25 934 1.1× 1.1k 1.4× 326 0.5× 1.1k 3.0× 512 1.8× 88 2.8k
Yang Yu China 24 618 0.7× 1.3k 1.7× 270 0.4× 255 0.7× 242 0.8× 93 1.9k
Roman W. Świniarski United States 11 817 0.9× 740 1.0× 188 0.3× 206 0.6× 613 2.1× 29 1.5k
Anne-Laure Jousselme Canada 16 335 0.4× 1.1k 1.4× 746 1.1× 152 0.4× 180 0.6× 83 1.9k
José Sanz Spain 30 967 1.1× 1.2k 1.6× 1.4k 2.0× 203 0.6× 208 0.7× 78 2.7k
Dominic Grenier Canada 12 255 0.3× 621 0.8× 494 0.7× 112 0.3× 121 0.4× 54 1.3k

Countries citing papers authored by Daniel Yeung

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Yeung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Yeung

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Yeung. A scholar is included among the top collaborators of Daniel Yeung 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 Daniel Yeung. Daniel Yeung 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.
Chan, Patrick P. K., et al.. (2025). Real-world nighttime image dehazing using contrastive and adversarial learning. Pattern Recognition. 165. 111596–111596. 4 indexed citations
2.
Yeung, Daniel, et al.. (2018). Facilitating integration of regulated pharmacy technicians into community pharmacy practice in Ontario: Results of an exploratory study. Canadian Pharmacists Journal / Revue des Pharmaciens du Canada. 151(3). 189–196. 5 indexed citations
3.
Yeung, Daniel, et al.. (2009). Sensitivity Analysis for Neural Networks. DIAL (Catholic University of Leuven). 85 indexed citations
4.
Tsang, Eric C.C., Degang Chen, & Daniel Yeung. (2008). Approximations and reducts with covering generalized rough sets. Computers & Mathematics with Applications. 56(1). 279–289. 110 indexed citations
5.
Wang, Defeng, Daniel Yeung, & Eric C.C. Tsang. (2007). Weighted Mahalanobis Distance Kernels for Support Vector Machines. IEEE Transactions on Neural Networks. 18(5). 1453–1462. 53 indexed citations
6.
Yeung, Daniel, Wing W. Y. Ng, Defeng Wang, Eric C.C. Tsang, & Xizhao Wang. (2007). Localized Generalization Error Model and Its Application to Architecture Selection for Radial Basis Function Neural Network. IEEE Transactions on Neural Networks. 18(5). 1294–1305. 152 indexed citations
7.
Jin, Shuyuan, Daniel Yeung, & Xizhao Wang. (2007). Network intrusion detection in covariance feature space. Pattern Recognition. 40(8). 2185–2197. 51 indexed citations
8.
Chan, Patrick P. K., et al.. (2006). Experimental Comparison Between Implicit and Explicit MCSs Construction Methods. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 2096. 2218–2221. 2 indexed citations
9.
Chen, Degang, Eric C.C. Tsang, Daniel Yeung, & Xizhao Wang. (2005). The parameterization reduction of soft sets and its applications. Computers & Mathematics with Applications. 49(5-6). 757–763. 468 indexed citations
10.
Yeung, Daniel, et al.. (2005). A HYBRID LANGUAGE MODEL BASED ON STATISTICS AND LINGUISTIC RULES. International Journal of Pattern Recognition and Artificial Intelligence. 19(1). 109–128. 4 indexed citations
11.
Yeung, Daniel, Zhiqiang Liu, Xizhao Wang, & Hong Yan. (2005). Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics. 1 indexed citations
12.
Chen, Degang, Wen‐Xiu Zhang, Daniel Yeung, & Eric C.C. Tsang. (2005). Rough approximations on a complete completely distributive lattice with applications to generalized rough sets. Information Sciences. 176(13). 1829–1848. 156 indexed citations
13.
Chung, Fu-Lai, et al.. (2002). Deriving multistage FNN models from Takagi and Sugeno's fuzzy systems. 2. 1259–1264. 3 indexed citations
14.
Yeung, Daniel, et al.. (2001). Sensitivity analysis of multilayer perceptron. International Joint Conference on Artificial Intelligence. 809–814. 3 indexed citations
15.
Tsang, Eric C.C., et al.. (2001). A general updating rule for discrete hopfield-type neural network with delay. International Joint Conference on Artificial Intelligence. 789–794.
16.
Luk, Robert W. P., et al.. (2000). Digital library access for Chinese visually impaired. 244–245. 3 indexed citations
17.
Yeung, Daniel, et al.. (1995). A knowledge matrix representation for a rule-mapped neural network. Neurocomputing. 7(2). 123–144. 1 indexed citations
18.
Yeung, Daniel, et al.. (1994). Knowledge matrix—an explanation & knowledge refinement facility for a rule induced neural network. National Conference on Artificial Intelligence. 889–894.
19.
Yeung, Daniel, et al.. (1994). A HYBRID COGNITIVE SYSTEM USING PRODUCTION RULES TO SYNTHESIZE NEOCOGNITRONS. International Journal of Neural Systems. 5(4). 345–355. 2 indexed citations
20.
Yeung, Daniel, et al.. (1994). Handwritten Chinese character recognition by rule-embedded Neocognitron. Neural Computing and Applications. 2(4). 216–226. 6 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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