3 ms·
Sure, but the fact that you get state of the art result without a convolutional prior ought to at least support the argument that the prior is not necessary
by murbard2 11y ago
Sure, but the fact that you get state of the art result without a convolutional prior ought to at least support the argument that the prior is not necessary
- sweezyjeezy 11y agoYou can get something like 5% error rate on MNIST with a well tuned linear classifier, it's not comparable with ImageNet. Note that the computer vision techniques used before convnets used things like SIFT features, which are another way of imposing a (sort-of) prior. I do believe that some sort of strong prior is necessary for the problem.