<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>

CC BY-SA 4.0
2018-08-10T03:26:05.300Z
2020-05-30T11:20:31.957Z
2020-05-30T11:20:31.957Z
juicedatom
<p>In which scenario, when assembling a CNN, would you want to have two adjacent pooling layers, without a convolutional layer in between?</p>

<deep-learning><convolutional-neural-networks><convolution><pooling>
In which scenario would you want to have two adjacent pooling layers?
Gaius
# 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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