Estimating classification images with generalized linear and additive models
K Knoblauch, LT Maloney - Journal of Vision, 2008 - jov.arvojournals.org
Conventional approaches to modeling classification image data can be described in terms
of a standard linear model (LM). We show how the problem can be characterized as a …
of a standard linear model (LM). We show how the problem can be characterized as a …
Improved classification images with sparse priors in a smooth basis
Classification images provide compelling insight into the strategies used by observers in
psychophysical tasks. However, because of the high-dimensional nature of classification …
psychophysical tasks. However, because of the high-dimensional nature of classification …
Parametric modelling of visual cortex at multiple scales
P Mineault - 2014 - escholarship.mcgill.ca
In the following thesis, I develop and apply a parametric systems identification framework to
study how visual stimuli are represented at the single-neuron, multi-neuron, and …
study how visual stimuli are represented at the single-neuron, multi-neuron, and …
[PDF][PDF] Improved classification images with sparse priors
PJ Mineault, S Barthelmé, CC Pack - 2009 - Citeseer
Classification images provide compelling insight into the strategies used by observers in
psychophysical tasks. However, because of the high-dimensional nature of classification …
psychophysical tasks. However, because of the high-dimensional nature of classification …
[PDF][PDF] Estimating classification images with generalized linear and additive
K Knoblauch, LT Maloney - 2008 - academia.edu
Conventional approaches to modeling classification image data can be described in terms
of a standard linear model (LM). We show how the problem can be characterized as a …
of a standard linear model (LM). We show how the problem can be characterized as a …