Nick Bostrom wrote:
> Doug Bailey wrote:
>
> > Got this off of Comline today:
> >
> > 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.
>
> 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.
>
Hey, I like this stuff. It's right up my alley. Anyway I say you can go in the opposite direction as long as your using a inbrid network and still have the database reference to the clear picture. It all depends on your resources, surely? btw, what is noice or do you mean noise?