Kyosuke Yamamoto
- Plant Science top 10%
- Analytical Chemistry top 5%
- Ecology
- Environmental Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- S. NinomiyaWei GuoYosuke YoshiokaNorio YamaguchiTakaharu KameokaAtsushi HashimotoYoshitsugu KimuraNaoki Watanabe
- Topics
- Smart Agriculture and AI (8 papers)Image Retrieval and Classification Techniques (3 papers)Water Quality Monitoring Technologies (2 papers)
In The Last Decade
Kyosuke Yamamoto
14 papers receiving 390 citations
Peers
Comparison fields: 5 of 57
- Plant Science 328
- Analytical Chemistry 125
- Ecology 92
- Environmental Engineering 49
- Computer Vision and Pattern Recognition 46
Countries citing papers authored by Kyosuke Yamamoto
This map shows the geographic impact of Kyosuke Yamamoto'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 Kyosuke Yamamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyosuke Yamamoto more than expected).
Fields of papers citing papers by Kyosuke Yamamoto
This network shows the impact of papers produced by Kyosuke Yamamoto. 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 Kyosuke Yamamoto. The network helps show where Kyosuke Yamamoto may publish in the future.
Co-authorship network of co-authors of Kyosuke Yamamoto
This figure shows the co-authorship network connecting the top 25 collaborators of Kyosuke Yamamoto. A scholar is included among the top collaborators of Kyosuke Yamamoto 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 Kyosuke Yamamoto. Kyosuke Yamamoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 7 | |
| 5 | 45 | |
| 6 | 93 | |
| 7 | 23 | |
| 8 | 195 | |
| 9 | 27 | |
| 10 | 0 | |
| 11 | 1 | |
| 12 | A wireless sensor network in a vineyard for smart viticultural management | 10 |
| 13 | Color image database construction for the strawberry breeding | 3 |
| 14 | Visual guideware as an information tool in the farm | 1 |
| 15 | Construction of the prototype system for the chromatic image analysis using Color Distribution Entropy | 3 |
| 16 | 2 |
About Kyosuke Yamamoto
Kyosuke Yamamoto is a scholar working on Computer Vision and Pattern Recognition, Plant Science and Media Technology, having authored 16 papers that have together received 414 indexed citations. Recurring topics across this work include Smart Agriculture and AI (8 papers), Image Retrieval and Classification Techniques (3 papers) and Water Quality Monitoring Technologies (2 papers). The work is most often cited by research in Analytical Chemistry (125 citations), Plant Science (328 citations) and Ecology (92 citations). Kyosuke Yamamoto has collaborated with scholars based in Japan, Australia and Egypt. Frequent co-authors include S. Ninomiya, Wei Guo, Yosuke Yoshioka, Norio Yamaguchi, Takaharu Kameoka, Atsushi Hashimoto, Yoshitsugu Kimura, Naoki Watanabe, Hajime Nagai and Satoru Sakai. Their work appears in journals such as PLoS ONE, Sensors and Computers and Electronics in Agriculture.
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.