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Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, NLP 2023-01-29
15:05
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Predictions and Attentions Acquired by Vision Transformer with Source-Target Attention from Dilated Convolutions on Small Data Sets
Tatsuki Shimura, Katsumi Tadamura, Toshikazu Samura (Yamaguchi Univ) NLP2022-104 NC2022-88
Vision Transformer (ViT) requires large data sets during pre-training phase to acquire high classification accuracy on a... [more] NLP2022-104 NC2022-88
pp.123-128
MSS, NLP 2022-03-29
14:15
Online Online Weighted Dice Loss for Segmentation from Noisy Labels
Toshikazu Samura, Katsumi Tadamura (Yamaguchi Univ.) MSS2021-77 NLP2021-148
Deep neural networks (DNNs) are easily affected by noisy labels during training. It degrades the classification performa... [more] MSS2021-77 NLP2021-148
pp.117-120
MSS, NLP
(Joint)
2020-03-09
15:45
Aichi  
(Cancelled but technical report was issued)
Two convolutional neural networks trained through Co-teaching perform a complementary role
Toshikazu Samura, Katsumi Tadamura (Yamaguchi Univ.) NLP2019-123
Deep learning technology needs big labeled data without noisy labels to improve its performance. However, the costs for ... [more] NLP2019-123
pp.61-64
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