That's actually not true, perceived pitch can be different from fundamental frequency, because of psychoacoustics.
E. g. you can have "missing fundamental" - https://en.wikipedia.org/wiki/Missing_fundamental - or other effects like "sum and difference tones", which are quite popular in spectralism / spectral music
Simple techniques like autocorrelation can still recover a missing fundamental. To answer the GP post, using neural networks for this task is overkill for simple, clean signals but it can be desirable if you need a) extremely high accuracy or b) robust results when there are signal degradations like background noise
We may perceive the same pitch (perhaps with a different timbre) even if the fundamental frequency is missing from a tone [1].
It seems to me like wikipedia agrees that even if the fundamental frequency is missing we could still use some kind of FFT to find the fundamental frequency being played (and therefore the perceived pitch). I might be missing something this is very far from my area of expertise :P
