Daniel Yeung

2.9k total citations
135 papers, 2.0k citations indexed

About

Daniel Yeung is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Daniel Yeung has authored 135 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Computer Vision and Pattern Recognition, 68 papers in Artificial Intelligence and 16 papers in Control and Systems Engineering. Recurrent topics in Daniel Yeung's work include Face and Expression Recognition (31 papers), Neural Networks and Applications (27 papers) and Image Retrieval and Classification Techniques (24 papers). Daniel Yeung is often cited by papers focused on Face and Expression Recognition (31 papers), Neural Networks and Applications (27 papers) and Image Retrieval and Classification Techniques (24 papers). Daniel Yeung collaborates with scholars based in China, Hong Kong and Canada. Daniel Yeung's co-authors include Wing W. Y. Ng, Patrick P. K. Chan, Fabio Roli, Xizhao Wang, Eric C.C. Tsang, Witold Pedrycz, Junjie Hu, Fei Zhang, Defeng Wang and Battista Biggio and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Daniel Yeung

129 papers receiving 1.9k 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 China 21 1.0k 700 311 266 242 135 2.0k
Sheng‐De Wang Taiwan 19 945 0.9× 756 1.1× 464 1.5× 260 1.0× 310 1.3× 126 2.5k
Yuk Ying Chung Australia 19 599 0.6× 607 0.9× 224 0.7× 181 0.7× 168 0.7× 125 1.6k
Patrick P. K. Chan China 21 634 0.6× 522 0.7× 269 0.9× 173 0.7× 332 1.4× 118 1.7k
Hadi Sadoghi Yazdi Iran 22 885 0.9× 489 0.7× 164 0.5× 197 0.7× 233 1.0× 184 2.0k
Zhaoquan Gu China 23 766 0.8× 547 0.8× 578 1.9× 358 1.3× 202 0.8× 165 2.2k
Ling Tian China 22 725 0.7× 582 0.8× 344 1.1× 176 0.7× 150 0.6× 122 1.7k
Nan Zhang China 24 760 0.7× 455 0.7× 163 0.5× 334 1.3× 221 0.9× 155 1.9k
Minnan Luo China 25 1.5k 1.5× 999 1.4× 368 1.2× 112 0.4× 179 0.7× 96 2.4k
Bin Gu China 17 847 0.8× 611 0.9× 174 0.6× 152 0.6× 115 0.5× 108 1.7k
Yuh‐Jye Lee Taiwan 15 1.0k 1.0× 727 1.0× 234 0.8× 89 0.3× 221 0.9× 44 1.7k

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.. (2023). Multi-proxy based deep metric learning. Information Sciences. 643. 119120–119120. 5 indexed citations
2.
Chan, Patrick P. K., et al.. (2022). Unsupervised Domain Adaptation for Gesture Identification Against Electrode Shift. IEEE Transactions on Human-Machine Systems. 52(6). 1271–1280. 10 indexed citations
3.
Liu, Weiwen, Yin Zhang, Jianling Wang, et al.. (2021). Item Relationship Graph Neural Networks for E-Commerce. IEEE Transactions on Neural Networks and Learning Systems. 33(9). 4785–4799. 47 indexed citations
4.
Chan, Patrick P. K., et al.. (2018). Shilling Attack Detection Using Rated Item Correlation for Collaborative Filtering. 3553–3558. 4 indexed citations
5.
Ng, Wing W. Y., Xing Tian, Witold Pedrycz, Xizhao Wang, & Daniel Yeung. (2018). Incremental Hash-Bit Learning for Semantic Image Retrieval in Nonstationary Environments. IEEE Transactions on Cybernetics. 49(11). 3844–3858. 18 indexed citations
6.
Ng, Wing W. Y., et al.. (2016). Dual autoencoders features for imbalance classification problem. Pattern Recognition. 60. 875–889. 75 indexed citations
7.
Chao, Lidia S., Derek F. Wong, C. L. Philip Chen, Wing W. Y. Ng, & Daniel Yeung. (2015). Benefiting feature selection by the discovery of false irrelevant attributes. International Journal of Wavelets Multiresolution and Information Processing. 13(4). 1550023–1550023. 1 indexed citations
8.
Ng, Wing W. Y., Zhimin He, Daniel Yeung, & Patrick P. K. Chan. (2014). Steganalysis classifier training via minimizing sensitivity for different imaging sources. Information Sciences. 281. 211–224. 15 indexed citations
9.
Sun, Binbin & Daniel Yeung. (2012). Sparse LS-SVM two-steps model selection method. 30. 460–465. 1 indexed citations
10.
Ng, Wing W. Y., Zhimin He, Patrick P. K. Chan, & Daniel Yeung. (2011). Blind steganalysis with high generalization capability for different image databases using L-GEM. 1768. 1690–1695. 6 indexed citations
11.
Chan, Patrick P. K., Bingzhong Jing, Wing W. Y. Ng, & Daniel Yeung. (2011). Depth estimation from a single image using defocus cues. 16. 1732–1738. 14 indexed citations
12.
Lin, Chih‐Min, Liyang Chen, & Daniel Yeung. (2010). Adaptive Filter Design Using Recurrent Cerebellar Model Articulation Controller. IEEE Transactions on Neural Networks. 21(7). 1149–1157. 29 indexed citations
13.
Jing, Bingzhong, et al.. (2009). RFID access authorization by face recognition. 302–307. 6 indexed citations
14.
Yeung, Daniel, et al.. (2007). Bankruptcy Prediction Using Multiple Intelligent Agent System via a Localized Generalization Error Approach. Digital Commons - Lingnan (Lingnan University). 1–6. 3 indexed citations
15.
Yeung, Daniel, Zhiqiang Liu, Xizhao Wang, & Hong Yan. (2006). Advances in machine learning and cybernetics : 4th International Conference, ICMLC 2005, Guangzhou, China, August 18-21, 2005 : revised selected papers. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1 indexed citations
16.
Wang, Defeng, Daniel Yeung, & Eric C.C. Tsang. (2006). Structured One-Class Classification. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 36(6). 1283–1295. 54 indexed citations
17.
Ng, Wing W. Y., et al.. (2006). Sphere Classification for Ambiguous Data. 12. 2571–2574. 6 indexed citations
18.
Yeung, Daniel, et al.. (1996). Three‐dimensional reconstruction of arteriovenous malformations from multiple stereotactic angiograms. Medical Physics. 23(10). 1797–1804. 6 indexed citations
19.
Shiu, Simon, Simon James, & Daniel Yeung. (1995). Modelling hybrid rule/frame-based expert systems using coloured Petri nets. 525–531. 8 indexed citations
20.
Yeung, Daniel, Jatinder Palta, James Fontanesi, & Larry E. Kun. (1994). Systematic analysis of errors in target localization and treatment delivery in stereotactic radiosurgery (SRS). International Journal of Radiation Oncology*Biology*Physics. 28(2). 493–498. 73 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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