| Global wheat head detection 2021: An improved dataset for benchmarking wheat head detection methods E David, M Serouart, D Smith, S Madec, K Velumani, S Liu, X Wang, ... Plant Phenomics, 2021 | 91 | 2021 |
| Global wheat head dataset 2021: more diversity to improve the benchmarking of wheat head localization methods E David, M Serouart, D Smith, S Madec, K Velumani, S Liu, X Wang, ... arXiv preprint arXiv:2105.07660, 2021 | 17 | 2021 |
| Global wheat head dataset 2021: An update to improve the benchmarking wheat head localization with more diversity E David, M Serouart, D Smith, S Madec, K Velumani, S Liu, X Wang, ... CoRR, 2021 | 7 | 2021 |
| Development of a high-throughput field phenotyping rover optimized for size-limited breeding fields as open-source hardware K Kuroki, K Yan, H Iwata, KK Shimizu, T Tameshige, S Nasuda, W Guo Breeding science 72 (1), 66-74, 2022 | 3 | 2022 |
| Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation R Akiyama, T Goto, T Tameshige, J Sugisaka, K Kuroki, J Sun, J Akita, ... Nature Communications 14 (1), 5792, 2023 | 2 | 2023 |
| Discovery of new interests by young scientists" application of phenotyping techniques for plant breeding". Y Tokuyama, M Okada, K Kuroki, S Komura, M Sato, A Nashiki, K Masuda, ... | | 2023 |
| PlantServation: time-series phenotyping using machine learning revealed seasonal pigment fluctuation in diploid and polyploid Arabidopsis R Akiyama, T Goto, T Tameshige, J Sugisaka, K Kuroki, J Sun, J Akita, ... bioRxiv, 2022.11. 21.517294, 2022 | | 2022 |
| The sea slugs of Shiroi Suna no Aquatope RB Salvador¹, K Kuroki | | 2022 |
| Rothamsted Repository Download E David, S Madec, P Sadeghi-Tehran, H Aasen, B Zheng, S Liu, ... | | 2020 |
Kentaro K. ShimizuProfessor at the University of Zurich, and Guest Professor at the Yokohama City University在 uzh.ch 的电子邮件经过验证
