42 citations · 42 across the 3 of their papers we have counts for
4 papers
Updating the standard neuron model in artificial neural networks
Raul Mohedano, Thomas Batard, Erik Velasco-Salido +4
From their inception in the 1950s, artificial neural networks (ANNs) started using the so-called point neuron model then prevalent in neuroscience, hoping that this analogy would a…
Hyperparameter-Free Losses for Model-Based Monocular Reconstruction
Eduard Ramon, Guillermo Ruiz, Thomas Batard +1
This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM). We dispense with the hyperparameters used in other works by expl…
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…