Kazuo Toraichi

186 total papers · 854 total citations
122 papers, 557 citations indexed

About

Kazuo Toraichi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computational Mechanics. According to data from OpenAlex, Kazuo Toraichi has authored 122 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Computer Vision and Pattern Recognition, 28 papers in Signal Processing and 28 papers in Computational Mechanics. Recurrent topics in Kazuo Toraichi's work include Image and Signal Denoising Methods (31 papers), Image Retrieval and Classification Techniques (25 papers) and Advanced Numerical Analysis Techniques (23 papers). Kazuo Toraichi is often cited by papers focused on Image and Signal Denoising Methods (31 papers), Image Retrieval and Classification Techniques (25 papers) and Advanced Numerical Analysis Techniques (23 papers). Kazuo Toraichi collaborates with scholars based in Japan, Slovenia and Singapore. Kazuo Toraichi's co-authors include Ryoichi Mori, Masaru Kamada, Keisuke Kameyama, Hiromitsu Yamada, Takahiko Horiuchi, M. Kamada, Yu-Ping Wang, Koichi Wada, Paul Kwan and Kazuhiko Yamamoto and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Kazuo Toraichi

97 papers receiving 514 citations

Author Peers

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

Author Last Decade Papers Cites
Kazuo Toraichi 363 91 88 77 59 122 557
Zhixin Zhou 243 0.7× 85 0.9× 34 0.4× 173 2.2× 101 1.7× 49 595
Guang Dai 311 0.9× 69 0.8× 60 0.7× 38 0.5× 174 2.9× 55 501
Ao Li 197 0.5× 48 0.5× 31 0.4× 61 0.8× 133 2.3× 61 520
Huang Wei 87 0.2× 106 1.2× 38 0.4× 52 0.7× 61 1.0× 69 533
Shujaat Khan 218 0.6× 38 0.4× 95 1.1× 14 0.2× 240 4.1× 43 697
Jingxin Zhang 111 0.3× 76 0.8× 105 1.2× 10 0.1× 76 1.3× 83 677
Bruce G. Batchelor 175 0.5× 36 0.4× 15 0.2× 45 0.6× 90 1.5× 65 538
Chao Wang 215 0.6× 40 0.4× 174 2.0× 21 0.3× 182 3.1× 64 568
Ramakrishna Kakarala 358 1.0× 58 0.6× 62 0.7× 97 1.3× 49 0.8× 56 548
Rafael Gadea Gironés 92 0.3× 12 0.1× 42 0.5× 33 0.4× 155 2.6× 63 651

Countries citing papers authored by Kazuo Toraichi

Since Specialization
Citations

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

Fields of papers citing papers by Kazuo Toraichi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kazuo Toraichi

This figure shows the co-authorship network connecting the top 25 collaborators of Kazuo Toraichi. A scholar is included among the top collaborators of Kazuo Toraichi 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 Kazuo Toraichi. Kazuo Toraichi 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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