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Found 12 papers, 2 papers with code
Reproducibility via neural fields of visual illusions induced by localized stimuli
The aim is to understand and model the visual phenomena observed in these experiments, emphasising their nonlinear nature.
Beyond $\ell_1$ sparse coding in V1
Compared to other methods, soft thresholding achieves this level of sparsity at the expense of much degraded reconstruction performance, that more likely than not is not acceptable in biological vision.
Cortical origins of MacKay-type visual illusions: A case for the non-linearity
To study the interaction between retinal stimulation by redundant geometrical patterns and the cortical response in the primary visual cortex (V1), we focus on the MacKay effect (Nature, 1957) and Billock and Tsou's experiments (PNAS, 2007).
Reproducing sensory induced hallucinations via neural fields
In this work, we focus on pattern formation in the visual cortex when the cortical activity is driven by a geometric visual hallucination-like stimulus.
A cortical-inspired sub-Riemannian model for Poggendorff-type visual illusions
We consider Wilson-Cowan-type models for the mathematical description of orientation-dependent Poggendorff-like illusions.
Cortical-inspired Wilson-Cowan-type equations for orientation-dependent contrast perception modelling
We consider the evolution model proposed in [9, 6] to describe illusory contrast perception phenomena induced by surrounding orientations.
A cortical-inspired model for orientation-dependent contrast perception: a link with Wilson-Cowan equations
We consider a differential model describing neuro-physiological contrast perception phenomena induced by surrounding orientations.
Cortical-inspired image reconstruction via sub-Riemannian geometry and hypoelliptic diffusion
In this paper we review several algorithms for image inpainting based on the hypoelliptic diffusion naturally associated with a mathematical model of the primary visual cortex.
A semidiscrete version of the Citti-Petitot-Sarti model as a plausible model for anthropomorphic image reconstruction and pattern recognition
Here, we propose a semi-discrete version of this theory, leading to a left-invariant structure over the group $SE(2, N)$, restricting to a finite number of rotations.
Generalized Fourier-Bessel operator and almost-periodic interpolation and approximation
We consider functions $f$ of two real variables, given as trigonometric functions over a finite set $F$ of frequencies.
Fourier descriptors based on the structure of the human primary visual cortex with applications to object recognition
In this paper we propose a supervised object recognition method using new global features and inspired by the model of the human primary visual cortex V1 as the semidiscrete roto-translation group $SE(2, N) = \mathbb Z_N\rtimes \mathbb R^2$.
Highly corrupted image inpainting through hypoelliptic diffusion
We present a new image inpainting algorithm, the Averaging and Hypoelliptic Evolution (AHE) algorithm, inspired by the one presented in [SIAM J.
