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I’m not saying you can’t use these existing techniques without understand all the theory, but you’re not going to be able to find new techniques.

For example, how would you know optimizing a convolution kernel is a good idea if you aren’t familiar with linear time invariant systems?



I think CNNs follow very naturally from the notion of shift/spatial invariance of visual processing. That doesn't require a mathematical understanding.


Image processing and shift invariance come from DSP.




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