Einoshin Suzuki

About

Einoshin Suzuki is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Einoshin Suzuki has authored 54 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 10 papers in Computational Theory and Mathematics. Recurrent topics in Einoshin Suzuki’s work include Anomaly Detection Techniques and Applications (16 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Data Mining Algorithms and Applications (8 papers). Einoshin Suzuki is often cited by papers focused on Anomaly Detection Techniques and Applications (16 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Data Mining Algorithms and Applications (8 papers). Einoshin Suzuki collaborates with scholars based in Japan, United States and China. Einoshin Suzuki's co-authors include Tetsu Matsukawa, Jan M. Żytkow, Masamichi Shimura, Takahiro Okabe, Yoichi Sato, Shin Ando, Katsuhiko Takabayashi, Wenbo Li, Bin Tong and Fabrice Guillet and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Sensors and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Co-authorship network of co-authors of Einoshin Suzuki i

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Fields of papers citing papers by Einoshin Suzuki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Einoshin Suzuki

Since Specialization

Citations

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

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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