Ryosuke Araki
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
- Neurology top 10%
- Brain Tumor Detection and Classification
Papers in
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- Robot Manipulation and Learning 6
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- Advanced Neural Network Applications 4
- Generative Adversarial Networks and Image Synthesis 2
- Co-authors
- Hideki Nakayama (2 shared papers)Hideaki Hayashi (2 shared papers)Leonardo Rundo (2 shared papers)Giancarlo Mauri (2 shared papers)Yujiro Furukawa (2 shared papers)Changhee Han (2 shared papers)Wataru Shimoda (1 shared paper)Takayoshi Yamashita (5 shared papers)
- Journals
- IEEE Access (1 paper)Advanced Robotics (1 paper)BOA (University of Milano-Bicocca) (1 paper)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)Journal of the Robotics Society of Japan (1 paper)
- Partner nations
- JapanItalySouth Sudan
In The Last Decade
Ryosuke Araki
8 papers receiving 382 citations
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 230
- Neurology 79
- Health Informatics 10
- Biophysics 32
- Artificial Intelligence 157
Countries citing papers authored by Ryosuke Araki
This map shows the geographic impact of Ryosuke Araki'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 Ryosuke Araki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryosuke Araki more than expected).
Fields of papers citing papers by Ryosuke Araki
This network shows the impact of papers produced by Ryosuke Araki. 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 Ryosuke Araki. The network helps show where Ryosuke Araki may publish in the future.
Co-authors
The 21 scholars most cited alongside Ryosuke Araki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 195 | |
| 2 | 2019 | 151 | |
| 3 | 2020 | 22 | |
| 4 | 2019 | 10 | |
| 5 | 2022 | 9 | |
| 6 | 2019 | 6 | |
| 7 | 2021 | 2 | |
| 8 | 2018 | 1 |
About Ryosuke Araki
Ryosuke Araki is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering and Biophysics, having authored 8 papers that have together received 396 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (6 papers), Advanced Neural Network Applications (4 papers), Soft Robotics and Applications (3 papers), Adversarial Robustness in Machine Learning (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Anomaly Detection Techniques and Applications (1 paper), Cell Image Analysis Techniques (1 paper) and Hand Gesture Recognition Systems (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (230 citations), Neurology (79 citations), Health Informatics (10 citations), Biophysics (32 citations) and Artificial Intelligence (157 citations). Ryosuke Araki has collaborated with scholars based in Japan, Italy and South Sudan. Frequent co-authors include Hideki Nakayama, Hideaki Hayashi, Leonardo Rundo, Giancarlo Mauri, Yujiro Furukawa, Changhee Han, Wataru Shimoda, Takayoshi Yamashita, Hironobu Fujiyoshi and Tsubasa Hirakawa. Their work appears in journals such as IEEE Access, Advanced Robotics, BOA (University of Milano-Bicocca), 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) and Journal of the Robotics Society of Japan.
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.