Masamichi Shimura

54 total papers · 632 total citations
28 papers, 261 citations indexed

About

Masamichi Shimura is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Masamichi Shimura has authored 28 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 3 papers in Computer Networks and Communications. Recurrent topics in Masamichi Shimura's work include Neural Networks and Applications (7 papers), AI-based Problem Solving and Planning (6 papers) and Nonlinear Dynamics and Pattern Formation (2 papers). Masamichi Shimura is often cited by papers focused on Neural Networks and Applications (7 papers), AI-based Problem Solving and Planning (6 papers) and Nonlinear Dynamics and Pattern Formation (2 papers). Masamichi Shimura collaborates with scholars based in Japan, United Kingdom and Philippines. Masamichi Shimura's co-authors include Masayuki Numao, J. Nagumo, Einoshin Suzuki, Riichiro Mizoguchi, Boonserm Kijsirikul, Kazuo Tanaka, C.V. Negoita, L. A. Zadeh, Kai Fu and Kambiz Badie and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Artificial Intelligence.

In The Last Decade

Masamichi Shimura

25 papers receiving 240 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Masamichi Shimura	118	56	43	42	33	28	261
Jiří Vomlel	240 2.0×	37 0.7×	53 1.2×	35 0.8×	32 1.0×	30	331
Shimon Schocken	167 1.4×	28 0.5×	40 0.9×	22 0.5×	37 1.1×	28	304
Jaak Tepandi	203 1.7×	60 1.1×	45 1.0×	47 1.1×	18 0.5×	19	323
Kim-Leng Poh	108 0.9×	68 1.2×	31 0.7×	16 0.4×	27 0.8×	27	307
Kristian Kersting	206 1.7×	41 0.7×	15 0.3×	31 0.7×	17 0.5×	26	300
Juan Fernández-Olivares	178 1.5×	47 0.8×	24 0.6×	20 0.5×	14 0.4×	34	290
Jürgen Wolff von Gudenberg	103 0.9×	124 2.2×	10 0.2×	102 2.4×	30 0.9×	40	308
Vladik Kreinovich	101 0.9×	32 0.6×	50 1.2×	53 1.3×	15 0.5×	24	270
Tao-Hsing Chang	207 1.8×	51 0.9×	45 1.0×	11 0.3×	24 0.7×	34	318
Hui Zhou	163 1.4×	85 1.5×	46 1.1×	9 0.2×	12 0.4×	26	291

Countries citing papers authored by Masamichi Shimura

Since Specialization

Citations

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

Fields of papers citing papers by Masamichi Shimura

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masamichi Shimura

This figure shows the co-authorship network connecting the top 25 collaborators of Masamichi Shimura. A scholar is included among the top collaborators of Masamichi Shimura 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 Masamichi Shimura. Masamichi Shimura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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