Answers.Body: <p>Assuming you're not referring to any particular type of pooling operation, it's possible that you could have, for example, a mean pool followed by a max or min pool. What this could do is combine the idea of reducing the dimensionality of your data from a holistic perspective with the mean pool, and then choosing the best of your averages with your max pool.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-08-10T03:26:05.300Z
Answers.LastActivityDate: 2020-05-30T11:20:31.957Z
Answers.LastEditDate: 2020-05-30T11:20:31.957Z
Answers.UserDisplayName: juicedatom
Body: <p>In which scenario, when assembling a CNN, would you want to have two adjacent pooling layers, without a convolutional layer in between?</p>
  
Tags: <deep-learning><convolutional-neural-networks><convolution><pooling>
Title: In which scenario would you want to have two adjacent pooling layers?
UserDisplayName: Gaius
ThreadText: # In which scenario would you want to have two adjacent pooling layers?
  
  (Asked by: username_0 on 2018-07-30)
  
  In which scenario, when assembling a CNN, would you want to have two adjacent pooling layers, without a convolutional layer in between?
  
  **Tags:** deep-learning, convolutional-neural-networks, convolution, pooling
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2018-08-10. Score: 3 | Accepted answer
  
  Assuming you're not referring to any particular type of pooling operation, it's possible that you could have, for example, a mean pool followed by a max or min pool. What this could do is combine the idea of reducing the dimensionality of your data from a holistic perspective with the mean pool, and then choosing the best of your averages with your max pool.
  
  
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