7 citations · 7 across the 2 of their papers we have counts for
3 papers
Joint Search of Data Augmentation Policies and Network Architectures
Taiga Kashima, Yoshihiro Yamada, Shunta Saito
The common pipeline of training deep neural networks consists of several building blocks such as data augmentation and network architecture selection. AutoML is a research field th…
Self-supervised Deep Learning for Reading Activity Classification
Md. Rabiul Islam, Shuji Sakamoto, Yoshihiro Yamada +4
Reading analysis can give important information about a user's confidence and habits and can be used to construct feedback to improve a user's reading behavior. A lack of labeled d…
ShakeDrop Regularization for Deep Residual Learning
Yoshihiro Yamada, Masakazu Iwamura, Takuya Akiba +1
Overfitting is a crucial problem in deep neural networks, even in the latest network architectures. In this paper, to relieve the overfitting effect of ResNet and its improvements…