Shakedrop Regularization for Deep Residual Learning

Shakedrop Regularization for Deep Residual Learning

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 (i.e., Wide ResNet, PyramidNet, and ResNeXt), we propose a new regularization method called ShakeDrop regularization. Sh...

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Bibliographic Details
Main Authors: Yoshihiro Yamada, Masakazu Iwamura, Takuya Akiba, Koichi Kise
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Computer vision
image classification
neural networks
Online Access:https://ieeexplore.ieee.org/document/8936428/

Internet

https://ieeexplore.ieee.org/document/8936428/

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