Topic: band-limited Gaussian noise

We compare how well human observers and neural networks recognize ImageNet images in filtered noise using the critical-band masking paradigm (Fletcher, 1940). We assess the spatial-frequency tuning of object recognition by measuring its noise tolerance at various frequencies. 16 observers and 4 neural networks performed 16-way categorization of 1050 ImageNet images perturbed by band-limited Gaussian noise of five strengths centered at seven spatial frequencies. We find that the noise sensitivity of object recognition is an inverted, U-shaped function of spatial frequency. Human observer perfor