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\section{Data augmentation}


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a)
Consider a traditional CNN network. It is known that we can use augmentation techniques (rotation, scaling...) in case we have only small amount of data. When do you think is the best time to perform the augmentation process? Explain. 
(Optional: give any other example of data augmentation) \\





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b)
There is a method in which we perform augmentation directly on test data. Why do you think it is possible to get better results because of this? What do we do at the end of the forward pass to get a classification result?


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