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We present a simple mathematical model for the mammalian low visual pathway,taking into account its key elements: retina, lateral geniculate nucleus (LGN),primary visual cortex (V1). The analogies between the cortical level of thevisual system and the structure of popular CNNs, used in image classificationtasks, suggests the introduction of an additional preliminary convolutionalmodule inspired to precortical neuronal circuits to improve robustness withrespect to global light intensity and contrast variations in the input images.We validate our hypothesis on the popular databases MNIST, FashionMNIST andSVHN, obtaining significantly more robust CNNs with respect to thesevariations, once such extra module is added.

A precortical module for robust CNNs to light variations