I was reading an article about deep learning and I've encountered this sentence:

Usually, deep learning models use dropout on the fully connected layers, but is also possible to use dropout after the max-pooling layers, creating image noise augmentation.

I don't know the meaning of "creating image noise augmentation" part. Is "creating images noise augmenation" the sequence of using dropout after the max-pooling layers or is it going to come alongside it?


"creating image noise augmentation" is the result of the process, though possibly an un-intended consequence.

What is also not entirely clear, is whether "creating image noise augmentation" would be a result of both options, or (more likely) only a result of the latter option.

And for completeness, but is also possible to use ... should read: but _it_ is also possible to use ...

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