Angela Y. Wu

10.5k total citations · 2 hit papers
53 papers, 6.9k citations indexed

About

Angela Y. Wu is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Theory and Mathematics. According to data from OpenAlex, Angela Y. Wu has authored 53 papers receiving a total of 6.9k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computer Vision and Pattern Recognition, 15 papers in Computer Graphics and Computer-Aided Design and 13 papers in Computational Theory and Mathematics. Recurrent topics in Angela Y. Wu's work include Digital Image Processing Techniques (16 papers), Computational Geometry and Mesh Generation (15 papers) and Medical Image Segmentation Techniques (9 papers). Angela Y. Wu is often cited by papers focused on Digital Image Processing Techniques (16 papers), Computational Geometry and Mesh Generation (15 papers) and Medical Image Segmentation Techniques (9 papers). Angela Y. Wu collaborates with scholars based in United States, Israel and Hong Kong. Angela Y. Wu's co-authors include David M. Mount, Ruth Silverman, Nathan S. Netanyahu, Christine Piatko, Tapas Kanungo, Sunil Arya, Azriel Rosenfeld, Bhaskar Sen, Tsai-Hong Hong and T. Yung Kong and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Information Sciences.

In The Last Decade

Angela Y. Wu

51 papers receiving 6.3k citations

Hit Papers

An efficient k-means clustering algorithm: analysis and i... 1998 2026 2007 2016 2002 1998 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Angela Y. Wu United States 17 2.8k 2.0k 1.0k 719 601 53 6.9k
Ruth Silverman United States 14 2.6k 0.9× 2.0k 1.0× 1.0k 1.0× 586 0.8× 591 1.0× 27 6.5k
Nathan S. Netanyahu United States 23 3.1k 1.1× 2.2k 1.1× 1.2k 1.2× 735 1.0× 780 1.3× 90 7.5k
David M. Mount United States 29 3.7k 1.3× 2.3k 1.2× 1.7k 1.6× 858 1.2× 983 1.6× 123 9.1k
S. Sathiya Keerthi India 29 3.5k 1.2× 4.1k 2.0× 583 0.6× 455 0.6× 489 0.8× 72 9.7k
Christine Piatko United States 19 2.1k 0.7× 2.1k 1.0× 683 0.7× 531 0.7× 233 0.4× 57 5.8k
Tapas Kanungo United States 22 2.3k 0.8× 2.2k 1.1× 727 0.7× 603 0.8× 258 0.4× 75 5.9k
Edwin R. Hancock United Kingdom 43 4.6k 1.6× 2.4k 1.2× 967 0.9× 300 0.4× 531 0.9× 485 7.4k
Mark E. Shields United States 3 3.1k 1.1× 4.3k 2.1× 814 0.8× 416 0.6× 285 0.5× 6 10.7k
Mehdi Mirza Canada 5 3.9k 1.4× 3.1k 1.5× 719 0.7× 365 0.5× 310 0.5× 5 9.2k
D.P. Huttenlocher United States 27 4.6k 1.6× 1.1k 0.6× 490 0.5× 420 0.6× 1.1k 1.8× 43 7.3k

Countries citing papers authored by Angela Y. Wu

Since Specialization
Citations

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

Fields of papers citing papers by Angela Y. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Angela Y. Wu. 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 Angela Y. Wu. The network helps show where Angela Y. Wu may publish in the future.

Co-authorship network of co-authors of Angela Y. Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Angela Y. Wu. A scholar is included among the top collaborators of Angela Y. Wu 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 Angela Y. Wu. Angela Y. Wu 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.
Wu, Angela Y., et al.. (2023). Quasi-self-similar fractals containing "Y" have dimension larger than one. Discrete and Continuous Dynamical Systems. 44(4). 1073–1086.
2.
Mount, David M., et al.. (2006). A practical approximation algorithm for the LMS line estimator. Computational Statistics & Data Analysis. 51(5). 2461–2486. 24 indexed citations
3.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (2002). An efficient k-means clustering algorithm: analysis and implementation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 24(7). 881–892. 3878 indexed citations breakdown →
4.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (2002). A local search approximation algorithm for k-means clustering. 10–18. 261 indexed citations
5.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (2000). The analysis of a simple k -means clustering algorithm. 100–109. 67 indexed citations
6.
Mount, David M., Nathan S. Netanyahu, Ruth Silverman, & Angela Y. Wu. (2000). Chromatic nearest neighbor searching: A query sensitive approach☆☆A preliminary version of this paper appeared in the Proceedings of the 7th Canadian Conference on Computational Geometry, 1995, pp. 261–266.. Computational Geometry. 17(3-4). 97–119. 5 indexed citations
7.
Kanungo, Tapas, David M. Mount, Nathan S. Netanyahu, et al.. (1999). Computing nearest neighbors for moving points and applications to clustering. Symposium on Discrete Algorithms. 931–932. 16 indexed citations
8.
Wu, Angela Y. & Azriel Rosenfeld. (1998). Geodesic visibility in graphs. Information Sciences. 108(1-4). 5–12. 14 indexed citations
9.
Mount, David M., et al.. (1997). A practical approximation algorithm for the LMS line estimator. Symposium on Discrete Algorithms. 473–482. 11 indexed citations
10.
Melter, Robert A., Angela Y. Wu, & Longin Jan Latecki. (1997). Vision Geometry VI. 3168. 2 indexed citations
11.
Arya, Sunil, David M. Mount, Nathan S. Netanyahu, Ruth Silverman, & Angela Y. Wu. (1994). An optimal algorithm for approximate nearest neighbor searching. Symposium on Discrete Algorithms. 573–582. 389 indexed citations
12.
Rosenfeld, Azriel & Angela Y. Wu. (1994). Geodesic convexity in discrete spaces. Information Sciences. 80(1-2). 127–132. 2 indexed citations
13.
Wu, Angela Y. & Azriel Rosenfeld. (1988). Parallel processing of encoded bit strings. Pattern Recognition. 21(6). 559–565. 2 indexed citations
14.
Rosenfeld, Azriel, et al.. (1983). Fast language acceptance by shrinking cellular automata. Information Sciences. 30(1). 47–53. 2 indexed citations
15.
Wu, Angela Y., Tsai-Hong Hong, & Azriel Rosenfeld. (1982). Threshold Selection Using Quadtrees. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-4(1). 90–94. 40 indexed citations
16.
Rosenfeld, Azriel, et al.. (1982). A Medial Axis Transformation for Grayscale Pictures. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-4(4). 419–421. 12 indexed citations
17.
Rosenfeld, Azriel & Angela Y. Wu. (1981). Reconfigurable cellular computers. Information and Control. 50(1). 64–84. 5 indexed citations
18.
Wu, Angela Y., et al.. (1981). Parallel Computation of Contour Properties. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-3(3). 331–337. 6 indexed citations
19.
Wu, Angela Y., et al.. (1981). Image Approximation from Gray Scale ``Medial Axes''. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-3(6). 687–696. 7 indexed citations
20.
Wu, Angela Y. & Azriel Rosenfeld. (1979). Cellular graph automata. II. graph and subgraph isomorphism, graph structure recognition. Information and Control. 42(3). 330–353. 13 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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