While not physiologically accurate, deep neural networks have a long history of being inspired by the brain. Of particular interest to computer vision researchers are the behaviour of neurons in the V1 Visual Cortex when responding to visual stimuli. Understanding how V1 neurons encode visual stimuli might offer insight on how to improve design of computer vision algorithms and "neural" representations of visual data. It has been known that neurons in the V1 cortex exhibit responses that can be modeled by 2D-Gabor filters. Knowing that, we wonder what kinds of functions a population of spiking neurons with Gabor-like encoders would be able to perform on images. In this work we explore, via spiking neuron modeling methods as described in the...
A primary focus of neuroscience is understanding how information about the world is encoded in the a...
We present a computationally effective toy model of the visual system of a biological brain, that ca...
International audienceAccurate estimation of neuronal receptive fields is essential for understandin...
While not physiologically accurate, deep neural networks have a long history of being inspired by th...
Our goal is to understand the dynamics of neural computations in low-level vision. We study how the ...
In this thesis, we examine two kinds of models of the primary visual cor- tex: a deep neural network...
The human genome (containing around 1E10 bits of information) is unlikely to fully specify the conne...
The human genome (containing around 1E10 bits of information) is unlikely to fully specify the conne...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
This document serves two purposes. First, it describes a computational model of V1 and MT neurons. S...
Abstract—Recent empirical evidence supports the hypothesis that invariant visual object recognition ...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
Horizontal connections in the primary visual cortex have been hypothesized to play a number of compu...
• Neurons in the visual cortex have Gabor-like receptive fields. • Looking at the response propertie...
A primary focus of neuroscience is understanding how information about the world is encoded in the a...
We present a computationally effective toy model of the visual system of a biological brain, that ca...
International audienceAccurate estimation of neuronal receptive fields is essential for understandin...
While not physiologically accurate, deep neural networks have a long history of being inspired by th...
Our goal is to understand the dynamics of neural computations in low-level vision. We study how the ...
In this thesis, we examine two kinds of models of the primary visual cor- tex: a deep neural network...
The human genome (containing around 1E10 bits of information) is unlikely to fully specify the conne...
The human genome (containing around 1E10 bits of information) is unlikely to fully specify the conne...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
This document serves two purposes. First, it describes a computational model of V1 and MT neurons. S...
Abstract—Recent empirical evidence supports the hypothesis that invariant visual object recognition ...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
Horizontal connections in the primary visual cortex have been hypothesized to play a number of compu...
• Neurons in the visual cortex have Gabor-like receptive fields. • Looking at the response propertie...
A primary focus of neuroscience is understanding how information about the world is encoded in the a...
We present a computationally effective toy model of the visual system of a biological brain, that ca...
International audienceAccurate estimation of neuronal receptive fields is essential for understandin...