Andy M. Yip

3.7k total citations
47 papers, 1.8k citations indexed

About

Andy M. Yip is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Andy M. Yip has authored 47 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 11 papers in Computational Mechanics and 10 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Andy M. Yip's work include Medical Image Segmentation Techniques (12 papers), Sparse and Compressive Sensing Techniques (9 papers) and Image and Signal Denoising Methods (9 papers). Andy M. Yip is often cited by papers focused on Medical Image Segmentation Techniques (12 papers), Sparse and Compressive Sensing Techniques (9 papers) and Image and Signal Denoising Methods (9 papers). Andy M. Yip collaborates with scholars based in Singapore, United States and Hong Kong. Andy M. Yip's co-authors include Steve Horvath, Tony F. Chan, Michael K. Ng, Selim Esedoḡlu, Pei‐Yong Shi, Wouter Schul, Chew Lim Tan, You‐Wei Wen, Raymond H. Chan and Raymond H. Chan and has published in prestigious journals such as Journal of Biological Chemistry, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Virology.

In The Last Decade

Andy M. Yip

44 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andy M. Yip Singapore	23	628	421	420	280	235	47	1.8k
Tomer Hertz Israel	24	793 1.3×	695 1.7×	87 0.2×	380 1.4×	51 0.2×	50	2.8k
Hemant D. Tagare United States	24	1.1k 1.8×	1.3k 3.0×	56 0.1×	170 0.6×	189 0.8×	110	3.5k
Carl Taswell United States	14	245 0.4×	350 0.8×	193 0.5×	129 0.5×	27 0.1×	71	2.5k
Takashi Isobe Japan	34	313 0.5×	1.1k 2.5×	135 0.3×	145 0.5×	19 0.1×	232	4.2k
Alberto Pascual-Montano Spain	30	190 0.3×	3.7k 8.8×	79 0.2×	117 0.4×	73 0.3×	49	5.2k
David W. Gohara United States	20	164 0.3×	915 2.2×	63 0.1×	244 0.9×	48 0.2×	30	2.3k
Laxmi Parida United States	23	153 0.2×	979 2.3×	37 0.1×	484 1.7×	53 0.2×	142	2.3k
Mingyuan Zhou United States	22	641 1.0×	128 0.3×	65 0.2×	27 0.1×	313 1.3×	113	1.9k
William J. Godinez Germany	17	87 0.1×	466 1.1×	73 0.2×	67 0.2×	15 0.1×	35	1.0k
T. M. Murali United States	22	275 0.4×	1.9k 4.5×	62 0.1×	97 0.3×	90 0.4×	74	2.7k

Countries citing papers authored by Andy M. Yip

Since Specialization

Citations

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

Fields of papers citing papers by Andy M. Yip

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andy M. Yip. 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 Andy M. Yip. The network helps show where Andy M. Yip may publish in the future.

Co-authorship network of co-authors of Andy M. Yip

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

All Works

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20 of 20 papers shown

Cheung, Ka Chun, et al.. (2023). Transfer Learning With Singular Value Decomposition of Multichannel Convolution Matrices. Neural Computation. 35(10). 1678–1712.

Gupta, Devendra, Laurent Dembélé, Annemarie Voorberg-van der Wel, et al.. (2019). The Plasmodium liver-specific protein 2 (LISP2) is an early marker of liver stage development. eLife. 8. 41 indexed citations

Yip, Andy M., et al.. (2014). Modulation of inflammation and pathology during dengue virus infection by p38 MAPK inhibitor SB203580. Antiviral Research. 110. 151–157. 31 indexed citations

Kim, Youngmee, Shovanlal Gayen, CongBao Kang, et al.. (2013). NMR Analysis of a Novel Enzymatically Active Unlinked Dengue NS2B-NS3 Protease Complex. Journal of Biological Chemistry. 288(18). 12891–12900. 90 indexed citations

Ng, Michael K., et al.. (2012). A Semisupervised Segmentation Model for Collections of Images. IEEE Transactions on Image Processing. 21(6). 2955–2968. 13 indexed citations

Lee, Hwee Kuan, et al.. (2011). Subspace learning for Mumford–Shah-model-based texture segmentation through texture patches. Applied Optics. 50(21). 3947–3947. 2 indexed citations

Wen, You‐Wei, Raymond H. Chan, & Andy M. Yip. (2011). A Primal–Dual Method for Total-Variation-Based Wavelet Domain Inpainting. IEEE Transactions on Image Processing. 21(1). 106–114. 37 indexed citations

Yip, Andy M., et al.. (2010). Automatic measurement of volume percentage stroma in endometrial images using texture segmentation. Journal of Microscopy. 241(2). 171–178. 4 indexed citations

Lee, Hwee Kuan, et al.. (2010). Semi-Supervised subspace learning for Mumford-Shah model based texture segmentation. Optics Express. 18(5). 4434–4434. 6 indexed citations

10.

Wen, You‐Wei, Chaoqiang Liu, & Andy M. Yip. (2010). Fast splitting algorithm for multiframe total variation blind video deconvolution. Applied Optics. 49(15). 2761–2761. 8 indexed citations

11.

Yip, Andy M., et al.. (2009). Supervised Texture Segmentation Using the Subspace Mumford-Shah Model.. National University of Singapore. 554–560. 4 indexed citations

12.

Chan, Raymond H., You‐Wei Wen, & Andy M. Yip. (2009). A Fast Optimization Transfer Algorithm for Image Inpainting in Wavelet Domains. IEEE Transactions on Image Processing. 18(7). 1467–1476. 23 indexed citations

13.

Poh, Mee Kian, Andy M. Yip, Summer L. Zhang, et al.. (2009). A small molecule fusion inhibitor of dengue virus. Antiviral Research. 84(3). 260–266. 118 indexed citations

14.

Yip, Andy M., et al.. (2008). A Multiresolution Stochastic Level Set Method for Mumford–Shah Image Segmentation. IEEE Transactions on Image Processing. 17(12). 2289–2300. 44 indexed citations

15.

Zhang, Li, Andy M. Yip, & Chew Lim Tan. (2007). Photometric and geometric restoration of document images using inpainting and shape-from-shading. National Conference on Artificial Intelligence. 1121–1126. 4 indexed citations

16.

Chan, Tony F., et al.. (2007). Superresolution image reconstruction using fast inpainting algorithms. Applied and Computational Harmonic Analysis. 23(1). 3–24. 38 indexed citations

17.

Yip, Andy M., et al.. (2007). Strategies for Identifying Statistically Significant Dense Regions in Microarray Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 4(3). 415–429. 5 indexed citations

18.

Yip, Andy M. & Steve Horvath. (2007). Gene network interconnectedness and the generalized topological overlap measure. BMC Bioinformatics. 8(1). 22–22. 472 indexed citations

19.

Yip, Andy M. & Steve Horvath. (2006). The Generalized Topological Overlap Matrix for Detecting Modules in Gene Networks.. 451–457. 19 indexed citations

20.

Yip, Andy M., Chris Ding, & Tony F. Chan. (2006). Dynamic cluster formation using level set methods. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(6). 877–889. 37 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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