No.  Most of layers in a CNN perform convolutions with kernels.  This is not the same as standard DNNs that do a full matrix multiply.<p>Convolutional kernels allow you to use many fewer variables to perform the forward layer operation; and CNNs tie these trainable variables across layers.  Training is not only faster, but also more robust because you have less parameters to learn.