Data augmentation enables CNNs to adapt to varying architectures and data amounts without hyperparameter fine-tuning, unlike weight decay and dropout.
Wide residual networks
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Further advantages of data augmentation on convolutional neural networks
Data augmentation enables CNNs to adapt to varying architectures and data amounts without hyperparameter fine-tuning, unlike weight decay and dropout.