Masaru Shimbo
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Management Science and Operations Research top 5%
- Statistics and Probability top 5%
- Signal Processing top 10%
- Co-authors
- Masaaki MiyakoshiMineichi KudoJun ToyamaTetsuya MuraiGermano ResconiHideo KanemitsuT. MuraiHiroki Hayashi
- Topics
- Rough Sets and Fuzzy Logic (9 papers)Fuzzy Logic and Control Systems (7 papers)Logic, Reasoning, and Knowledge (6 papers)
In The Last Decade
Masaru Shimbo
42 papers receiving 435 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 298
- Computational Theory and Mathematics 157
- Management Science and Operations Research 148
- Statistics and Probability 77
- Signal Processing 73
Countries citing papers authored by Masaru Shimbo
This map shows the geographic impact of Masaru Shimbo'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 Masaru Shimbo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masaru Shimbo more than expected).
Fields of papers citing papers by Masaru Shimbo
This network shows the impact of papers produced by Masaru Shimbo. 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 Masaru Shimbo. The network helps show where Masaru Shimbo may publish in the future.
Co-authorship network of co-authors of Masaru Shimbo
This figure shows the co-authorship network connecting the top 25 collaborators of Masaru Shimbo. A scholar is included among the top collaborators of Masaru Shimbo 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 Masaru Shimbo. Masaru Shimbo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 89 | |
| 9 | Construction of nonlinear discrimination function based on the MDL criterion. | 3 |
| 10 | Knowledge-based enhancement of low spatial resolution images | 2 |
| 11 | Piecewise linear classifiers preserving high local recognition rates | 1 |
| 12 | An Audio Coding Using Wavelet Packets | 1 |
| 13 | 4 | |
| 14 | Two Methods for Finding Local and Global Maxima of a Multimodal Function of One Variable Based on the Concept of a Unimodal Region | 0 |
| 15 | 16 | |
| 16 | 3 | |
| 17 | 10 | |
| 18 | 1 | |
| 19 | 9 | |
| 20 | [Acoustic characteristics and the occurrence mechanism of the Velcro rale (author's transl)]. | 1 |
About Masaru Shimbo
Masaru Shimbo is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Signal Processing, having authored 46 papers that have together received 466 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (9 papers), Fuzzy Logic and Control Systems (7 papers) and Logic, Reasoning, and Knowledge (6 papers). The work is most often cited by research in Management Science and Operations Research (148 citations), Computational Theory and Mathematics (157 citations) and Statistics and Probability (77 citations). Masaru Shimbo has collaborated with scholars based in Japan and Italy. Frequent co-authors include Masaaki Miyakoshi, Mineichi Kudo, Jun Toyama, Tetsuya Murai, Germano Resconi, Hideo Kanemitsu, T. Murai, Hiroki Hayashi, Manabu Sato and Hideaki Konno. Their work appears in journals such as The Journal of the Acoustical Society of America, Pattern Recognition and Information Sciences.
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.