Data augmentation

Perform an optimized data augmentation

Data augmentation is useful but can be time-consuming thus slowing down your development. It is often necessary when confronted with a massive domain of use like an open world as it improves the robustness of a neural network. In order to scale down the cost of training you need adequate data augmentation.

When performing your data augmentation Saimple can:

1- Orient your data augmentation

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2- Measure the impact of each data augmentation

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3- Limit the computation time spent in training

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