Mie Sato

750 citations
58 papers · 500 indexed · h-index 11

Impact in

Papers in

Mie Sato

42 papers receiving 464 citations

Peers

Mie Sato
Comparison fields: 5 of 104
  • Computer Graphics and Computer-Aided Design 92
  • Computer Vision and Pattern Recognition 263
  • Human-Computer Interaction 37
  • Biophysics 34
  • Structural Biology 5
Replace Lisa Avila with:
Lisa Avila United States
Antônio Wilson Vieira Brazil
Alexander Bornik Austria
Hiroyuki Kubo Japan
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Junjun Pan China
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Citations per field
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Citations per year

Countries citing papers authored by Mie Sato

Since Specialization
Citations

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

Fields of papers citing papers by Mie Sato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mie Sato, 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 Mie Sato Line = papers co-authored together Mie Sato links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001175
2 200271
3 200037
4 200235
5 200027
6 199724
7 200222
8 201512
9 201711
10 201411
11 200110
12 20167
13 20214
14 20064
15 19993
16 20203
17 20163
18 20213
19 20103
20
A Feature Extraction Method Based on Fractal Dimension
20062

About Mie Sato

Mie Sato is a scholar working on Human-Computer Interaction, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Media Technology and Social Psychology, having authored 58 papers that have together received 500 indexed citations. Recurring topics across this work include Interactive and Immersive Displays (11 papers), Virtual Reality Applications and Impacts (10 papers), Advanced Vision and Imaging (10 papers), Computer Graphics and Visualization Techniques (9 papers), Advanced Optical Imaging Technologies (8 papers), Color perception and design (8 papers), Tactile and Sensory Interactions (7 papers) and Augmented Reality Applications (7 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (92 citations), Computer Vision and Pattern Recognition (263 citations), Human-Computer Interaction (37 citations), Biophysics (34 citations) and Structural Biology (5 citations). Mie Sato has collaborated with scholars based in Japan, United States and Brazil. Frequent co-authors include Arie Kaufman, Ingmar Bitter, Michael A. Bender, M. Nakajima, Ming Wan, Sarang Lakare, Ming Wan, Kevin T. McDonnell, Yu Watanabe and Atsushi Ito. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Photochemistry and Photobiology, The Journal of The Institute of Image Information and Television Engineers, International Journal of Biometrics and Zenodo (CERN European Organization for Nuclear Research).

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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