Improving Deep Learning using Generic Data Augmentation

20 Aug 2017 Luke Taylor Geoff Nitschke

Deep artificial neural networks require a large corpus of training data in order to effectively learn, where collection of such training data is often expensive and laborious. Data augmentation overcomes this issue by artificially inflating the training set with label preserving transformations... (read more)

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