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2 main differences may be outlined. 1.NN can work in 2 modes: learning and production. If convolution is used in learning, this is a completely different story. 2.As to production mode, kernel-based transformations are more general. You can write a sophisticated processing hardly imaginable with NN, but the nets are more natural. If you restrict the solution to this class, probably it will work like human vision.