Research Guide: Data Augmentation for Deep Learning

AutoAugment is an augmentation strategy that employs a search algorithm to find an augmentation policy that will yield the best results on the model. Each policy has several sub-policies. One sub-policy is randomly chosen for each image. Each sub-policy consists of an image processing function and the probability that the functions are applied with. The image processing operations could be translation, shearing or rotation.