I really miss having the building block rationale of all the perception/classification/segmentation networks out there.

The only thing I've found really useful until now, is to put 2-fully connected layers if the classifier does now handle well classification... just because you needed a hidden perceptron layer for the XOR case.

I hope to find more examples like that. If you know them, please share!!