Doug Bailey wrote:
> Got this off of Comline today:
Actually, it has been know in the neural networks community a long
time that adding some noice often improves performance, especially
when you have a small number of learning samples. The noice prevents
the network from "overlearning", i.e. learning to recognize each
sample pattern individually. It forces the network to discover the
general regularities in the sample set.
A clear picture is still better than a blurry one. You can
always add noice afterwards if you like, but you can't go in the
opposite direction.
>
> A team from NEC {6701} and the University of Tokyo have
> discovered that applying noise to image recognition patterns
> through such artificial intelligence (AI) systems as neural
> networks will raise the accuracy of recognition systems.
> This runs counter to the prevailing belief that an image
> must be a neat as possible for clear pickup.