Deep neural networks (DNNs) are increasingly proposed as models of human vision,
bolstered by their impressive performance on image classification and object recognition …

The contrast sensitivity function (CSF) is a fundamental visual model explaining our ability to
detect small contrast patterns. CSFs found many applications in engineering, where they …

The electromagnetic spectrum of light from a rainbow is a continuous signal, yet we perceive
it vividly in several distinct colour categories. The origins and underlying mechanisms of this …

In this work, a machine learning methodology is proposed for the issue of color space
Euclidization. Given a color difference formula as reference distance law, the Euclidization …

The experiments allowed by current machine learning models imply a revival of the debate
on the causes of specific trends of human visual psychophysics. Machine learning facilitates …

Artificial neural networks (ANNs) are sensitive to perturbations and adversarial attacks. One
hypothesized solution to adversarial robustness is to align manifolds in the embedded …

Visual illusions in humans arise when interpreting out-of-distribution stimuli: if the observer
is adapted to certain statistics, perception of outliers deviates from reality. Recent studies …

Subjective image quality measures based on deep neural networks are very related to
models of visual neuroscience. This connection benefits engineering but, more interestingly …

We show that classical hue cancellation experiments lead to human-like opponent curves
even if the task is done by trivial (identity) artificial networks. Specifically, human-like …

We show that classical hue cancellation experiments lead to human-like opponent curves
even if the task is done by trivial (identity) artificial networks. Specifically, human-like …