Go Irie

18 papers and 173 indexed citations
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About

Go Irie is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Go Irie has authored 18 papers receiving a total of 173 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 7 papers in Signal Processing and 6 papers in Artificial Intelligence. Recurrent topics in Go Irie’s work include Domain Adaptation and Few-Shot Learning (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Multimodal Machine Learning Applications (3 papers). Go Irie is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Multimodal Machine Learning Applications (3 papers). Go Irie collaborates with scholars based in Japan, United States and South Korea. Go Irie's co-authors include Takeshi Kurashima, Tomoharu Iwata, Ko Fujimura, Yasuhiro Fujiwara, Kiyoharu Aizawa, Toshihiko Yamasaki, Akira Kojima, Makoto Onizuka, Daiki Ikami and Akisato Kimura and has published in prestigious journals such as IEEE Access, Pattern Recognition and International Journal of Computer Vision.

In The Last Decade

Co-authorship network of co-authors of Go Irie

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

Fields of papers citing papers by Go Irie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Go Irie

Since Specialization
Citations

This map shows the geographic impact of Go Irie'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 Go Irie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Go Irie 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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2026