Regularizing Deep Networks with Semantic Data Augmentation
IEEE transactions on pattern analysis and machine intelligence, pp. 1-1, 2020.
Data augmentation is widely known as a simple yet surprisingly effective technique for regularizing deep networks. In this paper, we propose a novel semantic data augmentation algorithm to complement traditional schemes, such as flipping, translation and rotation. The proposed method is inspired by the intriguing property that deep networ...More
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