Daiki Ikami

About

Daiki Ikami is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Daiki Ikami has authored 8 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Aerospace Engineering. Recurrent topics in Daiki Ikami’s work include Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers) and Advanced Vision and Imaging (2 papers). Daiki Ikami is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers) and Advanced Vision and Imaging (2 papers). Daiki Ikami collaborates with scholars based in Japan and United States. Daiki Ikami's co-authors include Kiyoharu Aizawa, Daiki Tanaka, Toshihiko Yamasaki, Shota Horiguchi, Go Irie, Takashi Shibata, Akari Asai and Qing Yu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

In The Last Decade

Co-authorship network of co-authors of Daiki Ikami i

Layout:

Gravity: 0.05 Iterations: 100 Initial Temp: 1000 Cooling: 0.99 Min Temp: 1

Fields of papers citing papers by Daiki Ikami

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daiki Ikami

Since Specialization

Citations

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

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by P.M.T. de Kok Breakdown of academic impact, for papers by Oreoluwa O. Adedoyin Breakdown of academic impact, for papers by Liana Menti Breakdown of academic impact, for papers by Xia-Rong Wang Breakdown of academic impact, for papers by Khalid Abdullah Breakdown of academic impact, for papers by Saif Abdul-Majeed Breakdown of academic impact, for papers by Stephen Ridge Breakdown of academic impact, for papers by X. Ke