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Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2023-09-08
10:05		 Osaka
(Primary: On-site, Secondary: Online)		 [Short Paper] Construction of Cell Nucleus Classifier using Complementary-Label Learning towards the Quantification of Grading for Follicular Lymphoma
Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-14		 In this paper, we report the cell type classification from a pathological image toward the subtype classification of mal... [more] MI2023-14
pp.1-2
EA, ASJ-H 2021-07-16
13:00		 Online Online Sound event detection based on complementary-label learning
Keigo Wakayama, Shoichiro Saito (NTT) EA2021-17		 Sound Event Detection (SED) is an important research field that can be applied to smart cities, and etc. SED estimate th... [more] EA2021-17
pp.77-82
IBISML 2021-03-02
10:00		 Online Online Learning from Noisy Complementary Labels with Robust Loss Functions
Hiroki Ishiguro (UTokyo), Takashi Ishida (UTokyo/RIKEN), Masashi Sugiyama (RIKEN/UTokyo) IBISML2020-34		 It has been demonstrated that large-scale labeled datasets facilitate the success of machine learning. However, collecti... [more] IBISML2020-34
pp.1-8
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