In papers such as ImageNet Classiﬁcation with Deep Convolutional Neural Networks
the training method seems to be basic backpropagation with stochastic gradient descent.
Even though CNNs are part of deep neural networks, is this purely because of a large number of hidden layers present? And does this mean that the backprop here falls under the category of deep learning because the network is deep, even though it does not follow the same pattern as the likes of a DBN using greedy layer-wise training, a true deep learning technique?
Thanks for the help and advice.