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I know that removing pooling layers will lead to an increase in dimensionality and subsequently, make the training to be more time-consuming. But I'm wondering if it worth it to remove pooling layers or not? does it lead to a higher accuracy?

Have you ever seen any relevant papers, articles, etc. about this issue? (I've searched and couldn't find much things except for this paper)

I even don't know how many pooling layers should I remove.

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Fatemeh Asgarinejad
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    Possible duplicate of [Can pooling ever increase accuracy in convolutional neural networks?](https://datascience.stackexchange.com/questions/44518/can-pooling-ever-increase-accuracy-in-convolutional-neural-networks) – Paul92 Jun 19 '19 at 22:18
  • That couldn't answer my problem. – Fatemeh Asgarinejad Jun 19 '19 at 22:24

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