Re:Attacking machine learning with adversarial examples
by lerid on Friday February 17, 2017 @03:24AM
(#13666773)
This seems like an obvious thing to try, but technically the convolutional structure already looks at different scales (in a way similar to mipmaps).
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Re:Attacking machine learning with adversarial examples
by jmcminis on Friday February 17, 2017 @01:05PM
(#13670306)
I've built a CNN before and that's not my understanding of it. The high frequency noise changes the output of the first layer on the CNN. This is what gets pooled as you go deeper into the net. Coarse graining is like getting rid of the weights you have for the first layer and replacing them with something uniform (average the smallest details together).