Differentiable RandAugment: Learning Selecting Weights and Magnitude Distributions of Image Transformations

Summary

Differentiable RandAugment (DRA) optimizes automatic data augmentation by learning transformation weights and magnitudes, outperforming standard RandAugment (RA) on ImageNet. This advanced technique enhances computer vision model performance with minimal computational cost.

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