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0 pointsenchiridion5y ago0 comments

So are you making LeNet shallower somehow?

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3 comments · 1 top-level

thedragonline5y ago· 2 in thread

The pooling layers are gone along with the first RELU. I've also reduced the number of outputs in each convolution layer.

enchiridionOP5y ago

That's quite a bit removed. I'd be surprised if it could do much of anything. I guess by using low res data you are also shrinking the problem.

thedragonline5y ago

I personally suspect that there are surprises in store for me by rooting around in this space. I have a .caffemodel that appears to correctly label better than chance, so my next step is to create a test dataset that's independent of original and see what happens. Personally, I find it unsettling that GPT 3 now contains 175 billion parameters. Why not go in the opposite direction and test the lower bound of what is possible?

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