Comments (2)
You can think of it as combining results of several convolutions which are far apart together effectively making a larger double-convolution - double in the sense of going one after the other due to having two RELUs. I think at least this would make sense. But the answer to why this works so good may be more complicated. And this also may not be a good decision in some situations - you should try - maybe, having larger kernels and less pooling works better in this game.
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I'm sure this will also work without pooling.
Using Pooling is only because at that time I want to have my network architecture as similar to the one used by image classification as possible.
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Related Issues (20)
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