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Data Augmentationに関するRyobotのブックマーク (1)

  • AutoAugment: Learning Augmentation Policies from Data

    Data augmentation is an effective technique for improving the accuracy of modern image classifiers. However, current data augmentation implementations are manually designed. In this paper, we describe a simple procedure called AutoAugment to automatically search for improved data augmentation policies. In our implementation, we have designed a search space where a policy consists of many sub-polic

    Ryobot
    Ryobot 2018/10/27
    On ImageNet, we attain a Top-1 accuracy of 83.54%. On CIFAR-10, we achieve an error rate of 1.48%
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