[Punoxysm]

The true value proposition of deep learning is not to avoid hand-coded features, but to make better use of scale in data and computational resources.

More specifically, adding SIFT or edge detection to your raw pixel input will almost always strictly improve a deep model's performance (though they might be redundant) at a not-particularly-large computational cost.

It wouldn't solve the adversarial example problem though, except to the extent that it makes calculating gradients harder.