We have seen many examples of excellent CNN performance for segmentation, image classification, style transfer, etc.

I wanted to start this thread to explore projects where CNNs fail or are not a good choice.

My current understanding is that a CNN is a great choice for computer vision tasks.

So, can an end-to-end CNN perform a Fourier Transform?

An FT is close to a vision task. **My idea is that frequencies are features/channels.**

I’ve searched and not found any references for Neural Networks performing FTs.

The Universal approximation theorem states that a feed forward NN should be able to perform any computation.

Is a feed forward NN a better choice?