42 citations · 70 across the 10 of their papers we have counts for
6 papers · 1 filter
Contrast Sensitivity Functions in Autoencoders
Qiang Li, Alex Gomez-Villa, Marcelo Bertalmio +1
Three decades ago, Atick et al. suggested that human frequency sensitivity may emerge from the enhancement required for a more efficient analysis of retinal images. Here we reasses…
Visual Information flow in Wilson-Cowan networks
Alexander Gomez-Villa, Marcelo Bertalmío, Jesús Malo
In this work we study the communication efficiency of a psychophysically-tuned cascade of Wilson-Cowan and Divisive Normalization layers that simulate the retina-V1 pathway. This i…
Visual illusions via neural dynamics: Wilson-Cowan-type models and the efficient representation principle
Marcelo Bertalmío, Luca Calatroni, Valentina Franceschi +3
In this work we have aimed to reproduce supra-threshold perception phenomena, specifically visual illusions, with Wilson-Cowan-type models of neuronal dynamics. We have found that…
Appropriate kernels for Divisive Normalization explained by Wilson-Cowan equations
Jesus Malo, Marcelo Bertalmio
The interaction between wavelet-like sensors in Divisive Normalization is classically described through Gaussian kernels that decay with spatial distance, angular distance and freq…
Derivatives and Inverse of Cascaded Linear+Nonlinear Neural Models
Marina Martinez-Garcia, Praveen Cyriac, Thomas Batard +2
In vision science, cascades of Linear+Nonlinear transforms are very successful in modeling a number of perceptual experiences [Carandini&Heeger12]. However, the conventional litera…
Derivatives and inverse of a linear-nonlinear multi-layer spatial vision model
Borja Galan, Marina Martinez-Garcia, Praveen Cyriac +3
Linear-nonlinear transforms are interesting in vision science because they are key in modeling a number of perceptual experiences such as color, motion or spatial texture. Here we…