Benson S. Y. Lam

623 total citations
27 papers, 440 citations indexed

About

Benson S. Y. Lam is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Benson S. Y. Lam has authored 27 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 5 papers in Management Science and Operations Research. Recurrent topics in Benson S. Y. Lam's work include Face and Expression Recognition (7 papers), Advanced Clustering Algorithms Research (5 papers) and Medical Image Segmentation Techniques (4 papers). Benson S. Y. Lam is often cited by papers focused on Face and Expression Recognition (7 papers), Advanced Clustering Algorithms Research (5 papers) and Medical Image Segmentation Techniques (4 papers). Benson S. Y. Lam collaborates with scholars based in Hong Kong, Australia and China. Benson S. Y. Lam's co-authors include Hong Yan, Amanda M. Y. Chu, Mike K. P. So, Siu Kai Choy, Connie Liu, Alan Wee‐Chung Liew, Wai Lo, Yongsheng Gao, Agnes Tiwari and David K. Smith and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Medical Imaging.

In The Last Decade

Benson S. Y. Lam

26 papers receiving 406 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benson S. Y. Lam Hong Kong 8 190 149 109 77 72 27 440
Esther de Ves Spain 11 237 1.2× 64 0.4× 48 0.4× 22 0.3× 51 0.7× 30 378
Hyuk-Yoon Kwon South Korea 8 163 0.9× 99 0.7× 39 0.4× 15 0.2× 177 2.5× 50 451
Abdulaziz Aljaloud Saudi Arabia 10 68 0.4× 41 0.3× 4 0.0× 77 1.0× 94 1.3× 15 314
Milton Román Cañizares Ecuador 12 9 0.0× 25 0.2× 13 0.1× 43 0.6× 74 1.0× 26 387
Yuhai Yu China 9 110 0.6× 91 0.6× 8 0.1× 7 0.1× 273 3.8× 14 406
Muhammad Mujahid Saudi Arabia 10 59 0.3× 92 0.6× 4 0.0× 9 0.1× 257 3.6× 32 508
Aruna Bhat India 10 97 0.5× 35 0.2× 7 0.1× 7 0.1× 117 1.6× 72 349
Mike Schaekermann United States 13 52 0.3× 159 1.1× 129 1.2× 4 0.1× 145 2.0× 24 409
Lucia Dettori United States 11 110 0.6× 70 0.5× 2 0.0× 64 0.8× 72 1.0× 28 383
Mo Zhang United States 11 95 0.5× 29 0.2× 4 0.0× 70 0.9× 153 2.1× 26 340

Countries citing papers authored by Benson S. Y. Lam

Since Specialization
Citations

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

Fields of papers citing papers by Benson S. Y. Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benson S. Y. Lam. 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 Benson S. Y. Lam. The network helps show where Benson S. Y. Lam may publish in the future.

Co-authorship network of co-authors of Benson S. Y. Lam

This figure shows the co-authorship network connecting the top 25 collaborators of Benson S. Y. Lam. A scholar is included among the top collaborators of Benson S. Y. Lam 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 Benson S. Y. Lam. Benson S. Y. Lam 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.
Lam, Benson S. Y., et al.. (2024). Linear discriminant analysis with trimmed and difference distribution modeling. Knowledge-Based Systems. 299. 112093–112093. 3 indexed citations
2.
Chu, Amanda M. Y., et al.. (2023). An automatic speech analytics program for digital assessment of stress burden and psychosocial health. SHILAP Revista de lepidopterología. 2(1). 15–15. 1 indexed citations
3.
Chu, Amanda M. Y., et al.. (2022). Vine copula statistical disclosure control for mixed-type data. Computational Statistics & Data Analysis. 176. 107561–107561. 1 indexed citations
4.
So, Mike K. P., et al.. (2021). Higher Education during the Pandemic: The Predictive Factors of Learning Effectiveness in COVID-19 Online Learning. Education Sciences. 11(8). 446–446. 72 indexed citations
5.
Chu, Amanda M. Y., Connie Liu, Mike K. P. So, & Benson S. Y. Lam. (2021). Factors for Sustainable Online Learning in Higher Education during the COVID-19 Pandemic. Sustainability. 13(9). 5038–5038. 50 indexed citations
6.
Chu, Amanda M. Y., et al.. (2021). Statistical disclosure control for continuous variables using an extended skew‐t copula. Applied Stochastic Models in Business and Industry. 38(1). 96–115. 1 indexed citations
7.
Lam, Benson S. Y., et al.. (2020). Who Leads the IPO News: Agenda-Building and Intermedia Agenda-Setting in a Routinised and Standardised News Context. Journalism Studies. 21(12). 1681–1704. 4 indexed citations
8.
Lam, Benson S. Y. & Alan Wee‐Chung Liew. (2020). A Fast Binary Quadratic Programming Solver Based on Stochastic Neighborhood Search. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(1). 32–49. 4 indexed citations
9.
Chu, Amanda M. Y., Benson S. Y. Lam, Agnes Tiwari, & Mike K. P. So. (2019). An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research. International Journal of Environmental Research and Public Health. 16(22). 4519–4519. 2 indexed citations
10.
Lam, Benson S. Y. & Siu Kai Choy. (2019). A Trimmed Clustering-Based l1-Principal Component Analysis Model for Image Classification and Clustering Problems with Outliers. Applied Sciences. 9(8). 1562–1562. 2 indexed citations
11.
Lo, Wai, et al.. (2019). The Dynamics of Political Elections: A Big Data Analysis of Intermedia Framing Between Social Media and News Media. Social Science Computer Review. 39(4). 627–647. 11 indexed citations
12.
Choy, Siu Kai, et al.. (2017). Fuzzy model-based clustering and its application in image segmentation. Pattern Recognition. 68. 141–157. 73 indexed citations
13.
Lam, Benson S. Y., et al.. (2016). Jump point detection using empirical mode decomposition. Land Use Policy. 58. 1–8. 4 indexed citations
14.
Lam, Benson S. Y., Yongsheng Gao, & Alan Wee‐Chung Liew. (2010). General Retinal Vessel Segmentation Using Regularization-Based Multiconcavity Modeling. IEEE Transactions on Medical Imaging. 29(7). 1369–1381. 6 indexed citations
15.
Lam, Benson S. Y. & Hong Yan. (2008). A Novel Vessel Segmentation Algorithm for Pathological Retina Images Based on the Divergence of Vector Fields. IEEE Transactions on Medical Imaging. 27(2). 237–246. 139 indexed citations
16.
Lam, Benson S. Y. & Hong Yan. (2006). A curve tracing algorithm using level set based affine transform. Pattern Recognition Letters. 28(2). 181–196. 6 indexed citations
17.
Lam, Benson S. Y. & Hong Yan. (2006). Improved Clustering Algorithm Based on Calculus of Variation. 900–903. 2 indexed citations
18.
Lam, Benson S. Y. & Hong Yan. (2006). Subdimension-based similarity measure for DNA microarray data clustering. Physical Review E. 74(4). 41906–41906. 4 indexed citations
19.
Lam, Benson S. Y. & Hong Yan. (2006). Assessment of Microarray Data Clustering Results Based on a New Geometrical Index for Cluster Validity. Soft Computing. 11(4). 341–348. 11 indexed citations
20.
Lam, Benson S. Y. & Hong Yan. (2005). Complex curve tracing based on a minimum spanning tree model and regularized fuzzy clustering. 3. 2091–2094. 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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