Masaki Ishii

1.8k total citations
109 papers, 1.1k citations indexed

About

Masaki Ishii is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Masaki Ishii has authored 109 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 13 papers in Molecular Biology and 11 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Masaki Ishii's work include Speech and Audio Processing (9 papers), Face and Expression Recognition (9 papers) and Robotics and Sensor-Based Localization (9 papers). Masaki Ishii is often cited by papers focused on Speech and Audio Processing (9 papers), Face and Expression Recognition (9 papers) and Robotics and Sensor-Based Localization (9 papers). Masaki Ishii collaborates with scholars based in Japan, France and United States. Masaki Ishii's co-authors include Tetsuo Tomiyama, Yoshiki Shimomura, Masaharu Yoshioka, Yasushi Umeda, Kazuhisa Sekimizu, Yasuhiko Matsumoto, Yasuhiro Yamaguchi, Masahiro Akishita, Yasuyoshi Ouchi and Hiroshi Yamamoto and has published in prestigious journals such as Chemical Communications, Scientific Reports and Biochemical and Biophysical Research Communications.

In The Last Decade

Masaki Ishii

99 papers receiving 989 citations

Peers

Masaki Ishii
Comparison fields: 5 of 151
  • Mechanical Engineering 265
  • Industrial and Manufacturing Engineering 229
  • Management of Technology and Innovation 189
  • Molecular Biology 183
  • Insect Science 129
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Michael A. Rosenman Australia View profile →
Citations per field, relative to Masaki Ishii
Masaki Ishii · 1×
Citations per year, relative to Masaki Ishii
Masaki Ishii · 1×

Countries citing papers authored by Masaki Ishii

Since Specialization
Citations

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

Fields of papers citing papers by Masaki Ishii

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masaki Ishii

This figure shows the co-authorship network connecting the top 25 collaborators of Masaki Ishii. A scholar is included among the top collaborators of Masaki Ishii 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 Masaki Ishii. Masaki Ishii 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
# Work Indexed citations
1 1
2 6
3 0
4 3
5 3
6 13
7 11
8 7
9 38
10 2
11 17
12 3
13
Mapping and correction method for mobile robot
1
14
Analysis of lip motion due to the influence of vocalization
1
15
A study of mobile robot localization using omnidirectional images
2
16
Modeling and Analysis of Direct Sampling Mixers including Parasitic Elements
0
17
The Design of Low Distoriton MOS Switches in Direct Sampling Mixers
1
18
Extraction of Facial Expression Categories and Generation of Emotion Map Using Self-Mapping
4
19 3
20 12

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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