Why do CNNs generalize so poorly to small image transformations?

Re:Why do CNNs generalize so poorly to small image transform... by dr_zoidberg on Monday June 11, 2018 @09:47AM (#17284122)

You made me think of the Margaret Thatcher Illusion, for which the best example I found was Dr. Phil Plait[0]. Funny thing, the idea of Capsule Networks (Hinton et al)[1, 2] seems to tackle some of these issues, though it's they're a bit young yet and more more work.

[0] https://www.opticalspy.com/opticals/dr-phil-plait-optical-il...

[1] https://arxiv.org/abs/1710.09829

[2] https://hackernoon.com/what-is-a-capsnet-or-capsule-network-...

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Re:Why do CNNs generalize so poorly to small image transform... by fallingfrog on Monday June 11, 2018 @10:00AM (#17284227)

I think that convolutional networks are really mostly a way to address space shift invariance too; and I even wonder if the same job could be done by some special purpose code that just runs the underlying neural net with a bunch of different rotations of the same image. That's probably how they do it now.. I feel like that's probably close to the optimal approach.

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