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Neural networks are not invariant to translations, but equivariant, Invariance vs Equivariance Suppose we have input $x$ and the output $y=f(x)$ of some map between spaces $X$ and $Y$. We apply transformation $T$ in the input domain. For general map,output will change in some complicated and unpredictable way. However, for certain class of maps, change of ...


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Traditional CNNs used for image classification (and related tasks) are composed of 1 or more fully connected layers (FCs), after the convolutional and pooling layers, which take as input the features extracted from the convolutional and pooling layers, in order to perform classification or regression. One problem with FCs in CNNs is that the number of ...


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