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Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)		 2023-03-14
10:20		 Tokyo The Univ. of Electro-Communications
(Primary: On-site, Secondary: Online)		 Study on a robust and accurate deep learning method
Shoma Noguchi, Shogo Taneda, Yukari Yamauchi (Nihon Univ.) NC2022-101		 In deep learning, there are many hyperparameters that must be determined in advance, and it is known that the accuracy v... [more] NC2022-101
pp.54-59
NC, MBE
(Joint)		 2023-03-15
10:30		 Tokyo The Univ. of Electro-Communications
(Primary: On-site, Secondary: Online)		 Proposal of Node Fusion in Sparse DenseNet
Shogo Taneda, Shoma Noguchi, Yukari Yamauchi (Nihon Univ.) NC2022-110		 Gao Huang et al. proposed a deep learning model called DenseNet. This deep learning model successfully prevents informat... [more] NC2022-110
pp.105-108
NC, MBE
(Joint)		 2021-03-03
13:00		 Online Online Hybrid Sparsity in Convolutional Neural Networks
Shoma Noguchi, Yukari Yamauchi (Nihon Univ.) NC2020-46		 Convolutional neural networks (CNNs) have achieved high accuracy in areas such as image classification and object detect... [more] NC2020-46
pp.21-24
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