研究成果
井澤班
- Hashimoto, S., & Itoh, J.
Managing water on plant leaf surfaces: Roles and regulation of hydrophobicity.
Journal of Experimental Botany. (2026).
https://doi.org/10.1093/jxb/erag112- Ogo, Y., Kawauchi, T., Mimura, M., Naito, K., Itoh, H., & Izawa, T.
A 65-kb deletion survey identifies a distal cis- regulatory region for red-light induction of Ghd7 , a key rice floral repressor.
Proceedings of the National Academy of Sciences, 122(33). (2025).
https://doi.org/10.1073/pnas.2423119122- Sun, R., Ding, Y., Mimura, M., Nishide, N., & Izawa, T.
Temporal transcriptome analysis reveals the two-phase action of florigens in rice flowering.
Theoretical and Applied Genetics, 138(5), 100. (2025).
https://doi.org/10.1007/s00122-025-04869-0- Toda, E., Koshimizu, S., Kinoshita, A., Higashiyama, T., Izawa, T., Yano, K., & Okamoto, T.
Transcriptional dynamics during karyogamy in rice zygotes.
Development, 152(2). (2025).
https://doi.org/10.1242/dev.204497- Ji, X., Bise, R., & Uchida, S.
Enhancing Reliability of Medical Image Diagnosis through Top-rank Learning with Rejection Module.
2025 19th International Conference on Machine Vision and Applications (MVA), 1-5. (2025).
https://doi.org/10.23919/MVA65244.2025.11175055- Matsuo, S., Togashi, R., Bise, R., Uchida, S., & Nomura, M.
Instance-wise Supervision-level Optimization in Active Learning.
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 4939-4947. (2025).
https://doi.org/10.1109/CVPR52734.2025.00465- Saito, Y., Matsuo, S., Uchida, S., & Suehiro, D.
Bounding the Worst-class Error: A Boosting Approach.
2025 International Joint Conference on Neural Networks (IJCNN), 1-8. (2025).
https://doi.org/10.1109/IJCNN64981.2025.11228502- Kuwada, E., Takeshita, K., Kawakatsu, T., Uchida, S., & Akagi, T.
Identification of lineage‐specific cis - trans regulatory networks related to kiwifruit ripening initiation.
The Plant Journal, 120(5), 1987-1999. (2024).
https://doi.org/10.1111/tpj.17093- Miya, M., Hibara, K., & Itoh, J.
Preparation and Sectioning of Paraffin-Embedded Tissue for Histology and Histochemistry Rice (pp. 41-48). (2025a).
https://doi.org/10.1007/978-1-0716-4204-7_6- Miya, M., Hibara, K., & Itoh, J.
Spatial Analysis of Gene Expression by In Situ Hybridization
Rice (pp. 49-59). (2025b).
https://doi.org/10.1007/978-1-0716-4204-7_7- Shirakawa, T., & Uchida, S.
NoiseCollage: A Layout-Aware Text-to-Image Diffusion Model Based on Noise Cropping and Merging.
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8921-8930. (2024).
https://doi.org/10.1109/CVPR52733.2024.00852- Takezaki, S., Tanaka, K., & Uchida, S.
Self-Relaxed Joint Training: Sample Selection for Severity Estimation with Ordinal Noisy Labels.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2025, Arizona, USA) (2024).
https://doi.org/10.48550/arXiv.2410.21885- Takezaki, S., & Uchida, S.
An Ordinal Diffusion Model for Generating Medical Images with Different Severity Levels.
2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-5. (2024).
https://doi.org/10.1109/ISBI56570.2024.10635504- Tezuka, T., Sato, R., Itoh, J., Kobayashi, T., Watanabe, T., Chiba, K., Shimizu, H., Nabeta, T., Sunohara, H., Wabiko, H., Nagasawa, N., & Satoh-Nagasawa, N.
Adaxial-abaxial bipolar leaf genes encode a putative cytokinin receptor and HD-Zip III, and control the formation of ectopic shoot meristems in rice.
Development, 151(16). (2024).
https://doi.org/10.1242/dev.202607- Toba, M., Uchida, S., & Hayashi, H.
Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model.
2024 International Joint Conference on Neural Networks (IJCNN), 1-8. (2024).
https://doi.org/10.1109/IJCNN60899.2024.10650805