Hankook Lee

Rethinking Data Augmentation: Self-Supervision and Self-Distillation

2019 · arXiv (Cornell University)

Data augmentation techniques, e.g., flipping or cropping, which systematically enlarge the training dataset by explicitly generating more training samples, are effective in improving the generalization performance of deep neural networks. In the supervised setting, a …