In what scenario when assembling a DL CNN would you want to have two adjacent pooling layers, without a convolutional layer between?
In your question you didn’t specify the type of pooling thay you aren’t doing. So it’s possoble 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 dimensionally of your data from a holistic perspective with the mean pool and the. “Choose the best of the averages” with your max pool.