William K. Cheung

5.8k total citations
230 papers, 3.8k citations indexed

About

William K. Cheung is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, William K. Cheung has authored 230 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Computer Vision and Pattern Recognition, 69 papers in Artificial Intelligence and 56 papers in Information Systems. Recurrent topics in William K. Cheung's work include Advanced Vision and Imaging (22 papers), Complex Network Analysis Techniques (20 papers) and Image Retrieval and Classification Techniques (19 papers). William K. Cheung is often cited by papers focused on Advanced Vision and Imaging (22 papers), Complex Network Analysis Techniques (20 papers) and Image Retrieval and Classification Techniques (19 papers). William K. Cheung collaborates with scholars based in Hong Kong, China and United States. William K. Cheung's co-authors include Jiming Liu, Lai-Man Po, Bo Yang, Xuyuan Xu, Terence Cheung, Litong Feng, Lejian Liao, H.F. Li, J. Michael Janda and Sharon L. Abbott and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

William K. Cheung

210 papers receiving 3.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
William K. Cheung Hong Kong	31	1.1k	1.0k	840	500	498	230	3.8k
Roni Rosenfeld United States	36	617 0.6×	2.9k 2.8×	734 0.9×	274 0.5×	517 1.0×	134	5.5k
Steven Skiena United States	37	647 0.6×	2.1k 2.0×	407 0.5×	468 0.9×	219 0.4×	197	6.5k
Volker Röth Switzerland	36	670 0.6×	1.2k 1.2×	484 0.6×	79 0.2×	486 1.0×	133	4.4k
Leandro Nunes de Castro Brazil	26	445 0.4×	2.5k 2.4×	365 0.4×	168 0.3×	277 0.6×	138	5.7k
David H. Ackley United States	14	500 0.5×	2.4k 2.3×	252 0.3×	292 0.6×	662 1.3×	42	4.1k
Boris Mirkin Russia	24	563 0.5×	1.2k 1.1×	348 0.4×	238 0.5×	392 0.8×	94	3.1k
Zhili Zhou China	37	1.7k 1.6×	986 1.0×	566 0.7×	249 0.5×	201 0.4×	214	4.7k
Ping Luo China	39	539 0.5×	1.6k 1.5×	811 1.0×	124 0.2×	222 0.4×	265	5.7k
Charles Sutton United States	34	1.5k 1.3×	3.5k 3.4×	1.4k 1.6×	323 0.6×	688 1.4×	97	6.8k
Dipankar Dasgupta United States	36	468 0.4×	2.5k 2.4×	803 1.0×	135 0.3×	948 1.9×	133	6.3k

Countries citing papers authored by William K. Cheung

Since Specialization

Citations

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

Fields of papers citing papers by William K. Cheung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William K. Cheung. 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 William K. Cheung. The network helps show where William K. Cheung may publish in the future.

Co-authorship network of co-authors of William K. Cheung

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chen, Zhaoliang, Zhihao Wu, William K. Cheung, et al.. (2025). MSHTrans: Multi-Scale Hypergraph Transformer with Time-Series Decomposition for Temporal Anomaly Detection. 274–285.

Cheung, William K., et al.. (2024). Fast Randomized Low-Rank Adaptation of Pre-trained Language Models with PAC Regularization. 5236–5249.

Liu, Qun, et al.. (2024). GEAR: Learning graph neural network explainer via adjusting gradients. Knowledge-Based Systems. 302. 112368–112368. 1 indexed citations

Lyu, Aiping, et al.. (2023). Accurate and interpretable gene expression imputation on scRNA-seq data using IGSimpute. Briefings in Bioinformatics. 24(3). 6 indexed citations

Chen, Jiaxing, et al.. (2022). dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using time-course single-cell gene expression data. Briefings in Bioinformatics. 23(6). 16 indexed citations

Chen, Jiaxing, Liang Lan, Xin Zhou, et al.. (2021). DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data. Briefings in Bioinformatics. 22(6). 58 indexed citations

Mørch, Anders I., et al.. (2017). EssayCritic: Writing to learn with a knowledge-based design critiquing system. Educational Technology & Society. 20(2). 213–223. 26 indexed citations

Cheung, William K., et al.. (2012). A study of gender differences in ICT competency. 1. 12–14. 1 indexed citations

Liu, Kai, William K. Cheung, & Jiming Liu. (2012). Extracting behavioral motifs for characterizing human daily activities in smart environments. HKBU Institutional Repository (Hong Kong Baptist University). 1 indexed citations

10.

Cheung, William K., et al.. (2011). A study of ICT literacy in Arts and Science students. International Conference on Information Systems. 5–7. 2 indexed citations

11.

Cheung, William K., et al.. (2009). Web-based essay critiquing system and EFL students' writing: a quantitative and qualitative investigation. Computer Assisted Language Learning. 22(1). 57–72. 36 indexed citations

12.

Wong, Raymond K., et al.. (2009). Mobile information exchange and integration: from query to application layer. Australasian Database Conference. 92. 115–124. 2 indexed citations

13.

Cheung, William K., et al.. (2007). Automatic generation of artistic chinese calligraphy. The HKU Scholars Hub (University of Hong Kong). 82 indexed citations

14.

Li, Xin, William K. Cheung, & Jiming Liu. (2005). Towards solving large-scale POMDP problems via spatio-temporal belief state clustering. HKBU Institutional Repository (Hong Kong Baptist University). 17. 3 indexed citations

15.

Mao, Yuxin, William K. Cheung, Zhaohui Wu, & Jiming Liu. (2005). Dynamic sub-ontology evolution for collaborative problem solving. HKBU Institutional Repository (Hong Kong Baptist University). 1–8. 3 indexed citations

16.

Zhang, Xiaofeng & William K. Cheung. (2005). Learning global models based on distributed data abstractions. HKBU Institutional Repository (Hong Kong Baptist University). 1645–1646. 8 indexed citations

17.

Zhang, Xiaofeng, et al.. (2004). Web page organization and visualization using generative topographic mapping: A pilot study. HKBU Institutional Repository (Hong Kong Baptist University). 126–131.

18.

Cheung, William K. & Dit‐Yan Yeung. (1997). Recognition of handwritten digits using deformable models. 259–262. 1 indexed citations

19.

Cheung, William K., Dit Yan Yeung, & R.T. Chin. (1995). A unified framework for handwritten character recognition using deformable models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 344–348. 3 indexed citations

20.

Cheung, William K., et al.. (1995). PERFORMANCE OF MPEG-1 VIDEO ON MULTIACCESS INTEGRATED NETWORK. Asia-Pacific Conference on Communications. 628–631. 1 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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