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The Effectiveness of Data Augmentation in Image ...

The Effectiveness of Data Augmentation in Image Classification using DeepLearningJason WangStanford University450 Serra PerezGoogle1600 Amphitheatre this paper, we explore and compare multiple solutionsto the problem of data Augmentation in Image work has demonstrated the Effectiveness of dataaugmentation through simple techniques, such as cropping,rotating, and flipping input images. We artificially con-strain our access to data to a small subset of the ImageNetdataset, and compare each data Augmentation technique inturn. One of the more successful data augmentations strate-gies is the traditional transformations mentioned above. Wealso experiment with GANs to generate images of differentstyles. Finally, we propose a method to allow a neural net tolearn augmentations that best improve the classifier, whichwe call neural Augmentation .

training, 10k validation, and 10k test images of dimensions 64x64x3. There are a total of 500 images per class with 200 distinct classes. MNIST consists of 60k handwritten digits in the training set and 10k in the test set in grayscale with 10 classes with image dimensions of 28x28x1. To evaluate the effectiveness of augmentation techniques, we ...

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