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Data augmentation for neural network training – example for printed characters recognition

Data augmentation for neural network training – example for printed characters recognition

The most complicated component of the method is an accurate selection of the augmentation parameters for generating the training dataset from the initial samples. On the one hand, a number of samples must be sufficient for the neural network to learn even noisy images, on the other hand, it is necessary for the response for the other types of non-trivial input images to remain intact.

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