Whilst reading up on the Deep learning literature, I noticed that a few variations on the standard network structure that were created specifically to better model "Natural/Real Images". For example, this paper says that:
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difﬁcult to apply them to real images. ... [Our network] can better model the covariance structure of natural images.
The paper seems to imply that only real or natural images have a rich local covariance structure. If that's the case, then would a screenshot of a videogame count as a natural image? A digital painting? and in any case in there an algorithmic way to test for this "Naturalness"?
This may sound open-ended, so let eplicitly operationalize it: when given a training set of 2D pixel arrays, how to do determine if you should use a standard network structure or a structure intended for natural/real images?