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== Pooling ==
Capsnets reject the [[pooling layer]] strategy of conventional CNNs that reduces the amount of detail to be processed at the next higher layer. Pooling allows a degree of translational invariance (it can recognize the same object in a somewhat different ___location) and allows a larger number of feature types to be represented. Capsnet proponents argue that pooling:<ref name=":1"/>
* violates biological shape perception in that it has no intrinsic coordinate frame;
* provides invariance (discarding positional information) instead of equivariance (disentangling that information);
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