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Dive into the research topics where Daiki Suehiro is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Learning from majority label: A novel problem in multi-class multiple-instance learning
Shiku, K., Matsuo, S., Suehiro, D. & Bise, R., Apr 2026, In: Pattern Recognition. 172, 112425.Research output: Contribution to journal › Article › peer-review
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Bounding the Worst-class Error: A Boosting Approach
Saito, Y., Matsuo, S., Uchida, S. & Suehiro, D., 2025, International Joint Conference on Neural Networks, IJCNN 2025 - Proceedings. Institute of Electrical and Electronics Engineers Inc., (Proceedings of the International Joint Conference on Neural Networks).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer
Shiku, K., Nishimura, K., Suehiro, D., Tanaka, K. & Bise, R., 2025, Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025. Institute of Electrical and Electronics Engineers Inc., p. 4290-4299 10 p. (Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
2 Link opens in a new tab Citations (Scopus) -
COUNTING NETWORK FOR LEARNING FROM MAJORITY LABEL
Shiku, K., Matsuo, S., Suehiro, D. & Bise, R., 2024, 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 7025-7029 5 p. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Link opens in a new tab Citation (Scopus) -
Learning from Partial Label Proportions for Whole Slide Image Segmentation
Matsuo, S., Suehiro, D., Uchida, S., Ito, H., Terada, K., Yoshizawa, A. & Bise, R., 2024, Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Proceedings. Linguraru, M. G., Feragen, A., Glocker, B., Giannarou, S., Schnabel, J. A., Dou, Q. & Lekadir, K. (eds.). Springer Science and Business Media Deutschland GmbH, p. 372-382 11 p. (Lecture Notes in Computer Science; vol. 15011 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Link opens in a new tab Citation (Scopus)