I have the basic knowledgment of how an autoencoder works.
In several posts/books/papers is mentioned that, after the training, the encoder part can be used as a dimensionality reduction and the produced "codes" can be used as input in a classifier.
My question is, since the code is a sort of volumetric image (for example I could have a code of dimension 14 x 14 x 32) how can use it as input to a classifier different of CNNs? Could I use it, for example, with a SVM? If so, makes sense to reshape the code in order to have a feature vector?
I'm quite confuse here so, any information would be helpful.