Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring.First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we intro...
The natural world is filled with perfectly working, functional systems that are robust, accurate, an...
This thesis describes the development of a real-time vision system for computing optic flow. The com...
We propose a biologically motivated computational step, called nonclassical receptive field (non-CRF...
BACKGROUND:Dynamical systems like neural networks based on lateral inhibition have a large field of ...
Background: Dynamical systems like neural networks based on lateral inhibition have a large field of...
A large gap exists at present between computational theories of vision and their possible implemen...
We present a scheme for obstacle detection from optical flow which is based on strategies of biologi...
This paper integrates knowledge from physiology and psychophysics (i.e., visual perception) to propo...
This work deals with mathematical tools based both on partial differential equations and neural netw...
A neuro-physiologically inspired model is presented for the contrast enhancement of images. The cont...
International audienceStudies in biological vision have always been a great source of inspiration fo...
In this paper, the authors present information processing strategies, derived from neurobiology, whi...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
The following research gains insight from the human visual system by studying the interactions invol...
We propose a biologically motivated computational step, called nonclassical receptive field (non-CRF...
The natural world is filled with perfectly working, functional systems that are robust, accurate, an...
This thesis describes the development of a real-time vision system for computing optic flow. The com...
We propose a biologically motivated computational step, called nonclassical receptive field (non-CRF...
BACKGROUND:Dynamical systems like neural networks based on lateral inhibition have a large field of ...
Background: Dynamical systems like neural networks based on lateral inhibition have a large field of...
A large gap exists at present between computational theories of vision and their possible implemen...
We present a scheme for obstacle detection from optical flow which is based on strategies of biologi...
This paper integrates knowledge from physiology and psychophysics (i.e., visual perception) to propo...
This work deals with mathematical tools based both on partial differential equations and neural netw...
A neuro-physiologically inspired model is presented for the contrast enhancement of images. The cont...
International audienceStudies in biological vision have always been a great source of inspiration fo...
In this paper, the authors present information processing strategies, derived from neurobiology, whi...
The study of the visual system of the brain has attracted the attention and interest of many neuro-s...
The following research gains insight from the human visual system by studying the interactions invol...
We propose a biologically motivated computational step, called nonclassical receptive field (non-CRF...
The natural world is filled with perfectly working, functional systems that are robust, accurate, an...
This thesis describes the development of a real-time vision system for computing optic flow. The com...
We propose a biologically motivated computational step, called nonclassical receptive field (non-CRF...