Washington Mio

5.2k citations
69 papers · 3.1k · 1 hit paper · h-index 16

Impact in

Papers in

Washington Mio

66 papers receiving 3.0k citations

Washington Mio's Hit Papers

Statistical shape analysis: clustering, learning, and testing 2005 · 1.9k citations
1.9k0+7+14Years since publication50010001.5k

Peers

Washington Mio
Comparison fields: 5 of 163
  • Geometry and Topology 1.5k
  • Paleontology 351
  • Computer Vision and Pattern Recognition 979
  • Anthropology 191
  • Computational Mechanics 303
Replace Anuj Srivastava with:
Anuj Srivastava United States
Charles R. Giardina United States
Ian L. Dryden United Kingdom
Frank P. Kuhl United States
Guido Ranzuglia Italy
Matteo Dellepiane Italy
Marco Callieri Italy
Massimiliano Corsini Italy
Fabio Ganovelli Italy
Nina Amenta United States
Washington Mio relative to Anuj Srivastava United States Anuj Srivastava's profile →
Citations per field
00.5×1.5×
Anuj Srivastava · 1×
Citations per year

Countries citing papers authored by Washington Mio

Since Specialization
Citations

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

Fields of papers citing papers by Washington Mio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Washington Mio. 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 Washington Mio. The network helps show where Washington Mio may publish in the future.

Co-authors

The 25 scholars most cited alongside Washington Mio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Washington Mio Line = papers co-authored together Washington Mio links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Statistical shape analysis: clustering, learning, and testing
Hit paper breakdown →
20051944
2 2004289
3 2006124
4 201374
5 201670
6 201562
7 201658
8 199653
9 201652
10 201544
11 201840
12 200434
13 201731
14 201727
15 198721
16 201520
17 200413
18 199313
19 201010
20 200810

About Washington Mio

Washington Mio is a scholar working on Computer Vision and Pattern Recognition, Geometry and Topology, Mathematical Physics, Computational Mechanics and Computational Theory and Mathematics, having authored 69 papers that have together received 3.1k indexed citations. Recurring topics across this work include Morphological variations and asymmetry (22 papers), Medical Image Segmentation Techniques (11 papers), Face and Expression Recognition (11 papers), Topological and Geometric Data Analysis (11 papers), Homotopy and Cohomology in Algebraic Topology (10 papers), Image Retrieval and Classification Techniques (10 papers), Image Processing and 3D Reconstruction (7 papers) and 3D Shape Modeling and Analysis (7 papers). The work is most often cited by research in Geometry and Topology (1.5k citations), Paleontology (351 citations), Computer Vision and Pattern Recognition (979 citations), Anthropology (191 citations) and Computational Mechanics (303 citations). Washington Mio has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Anuj Srivastava, S. K. Joshi, Xiuwen Liu, Eric Klassen, Shantanu H. Joshi, Mao Li, Benedikt Hallgrímsson, Luke Mander, Qiuping Xu and John Bryant. Their work appears in journals such as International Journal of Computer Vision, Transactions of the American Mathematical Society, Mathematical Proceedings of the Cambridge Philosophical Society, Applied and Computational Harmonic Analysis and Royal Society Open Science.

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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