Fubito Toyama
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Cellular and Molecular Neuroscience
- Radiology, Nuclear Medicine and Imaging
- Reproductive Medicine
- Co-authors
- Chikafumi ChibaShoji KidoFumiaki MaruoMd Rafiqul IslamKenta NakamuraKiyoshi KatōKeisuke SakuraiAkihiko Watanabe
- Topics
- Sperm and Testicular Function (8 papers)Advanced Vision and Imaging (7 papers)Video Analysis and Summarization (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- JapanUnited StatesFinland
In The Last Decade
Fubito Toyama
37 papers receiving 387 citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 170
- Computer Vision and Pattern Recognition 124
- Cellular and Molecular Neuroscience 44
- Radiology, Nuclear Medicine and Imaging 44
- Reproductive Medicine 35
Countries citing papers authored by Fubito Toyama
This map shows the geographic impact of Fubito Toyama'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 Fubito Toyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fubito Toyama more than expected).
Fields of papers citing papers by Fubito Toyama
This network shows the impact of papers produced by Fubito Toyama. 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 Fubito Toyama. The network helps show where Fubito Toyama may publish in the future.
Co-authorship network of co-authors of Fubito Toyama
This figure shows the co-authorship network connecting the top 25 collaborators of Fubito Toyama. A scholar is included among the top collaborators of Fubito Toyama 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 Fubito Toyama. Fubito Toyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 14 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 11 | |
| 11 | 7 | |
| 12 | 24 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 38 | |
| 16 | 48 | |
| 17 | 0 | |
| 18 | 0 | |
| 19 | 5 | |
| 20 | Layout analysis of tree-structured scene frames in comic images | 45 |
About Fubito Toyama
Fubito Toyama is a scholar working on Computer Vision and Pattern Recognition, Reproductive Medicine and Physiology, having authored 42 papers that have together received 400 indexed citations. Recurring topics across this work include Sperm and Testicular Function (8 papers), Advanced Vision and Imaging (7 papers) and Video Analysis and Summarization (5 papers). The work is most often cited by research in Space and Planetary Science (19 citations), Computer Vision and Pattern Recognition (124 citations) and Reproductive Medicine (35 citations). Fubito Toyama has collaborated with scholars based in Japan, United States and Finland. Frequent co-authors include Chikafumi Chiba, Shoji Kido, Fumiaki Maruo, Md Rafiqul Islam, Kenta Nakamura, Kiyoshi Katō, Keisuke Sakurai, Akihiko Watanabe, Panagiotis A. Tsonis and Kenta Nakamura. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.