Deep Learning

Learning where to look: a foveated visuomotor control model

In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large and crowded visual display. This task is usually implemented by scanning the different possible target identities at …

A dual foveal-peripheral visual processing model implements efficient saccade selection

In computer vision, the visual search task consists in extracting a scarce and specific visual information (the target) from a large and crowded visual display. This task is usually implemented by scanning the different possible target identities at …

A hierarchical, multi-layer convolutional sparse coding algorithm based on predictive coding

Sparse coding holds the idea that signals can be concisely described as a linear mixture of few components (called atoms) picked from a bigger set of primary kernels (called dictionary). This framework has long been used to model the strategy …

Modelling Complex Cells of Early Visual Cortex using Predictive Coding

Sparse Deep Predictive Coding To Model Visual Object Recognition

Convolutional Neural Network (CNN) are popular to model object recognition in the brain. They offer a flexible and convenient framework to model the hierarchical stacking of cortical areas that compose the Visual Ventral Stream. However, CNN suffers …

Top-down connection in Hierarchical Sparse Coding

The brain has to solve inverse problems to correctly interpret sensory data and infer the set of causes that generated the sensory inputs. When imposing sparse prior and hierarchical structure this problem is called Hierarchical Sparse Coding (HSC). …

From biological vision to unsupervised hierarchical sparse coding

The formation of connections between neural cells is essentially emerging from an unsupervised learning process. During the development of primary visual cortex (V1) of mammals, for example, one may observe the emergence of cells selective to …

On the Origins of Hierarchy in Visual Processing

Unsupervised Hierarchical Sparse Coding algorithm inspired by Biological Vision

The brain has to solve inverse problems to correctly interpret sensory data and infer the set of causes that generated the sensory inputs. Such a problem is typically ill-posed, and thus requires constraint the narrow down the number of solutions. …

Controlling an aerial robot with human gestures using bio-inspired algorithm

Improve performances of existing recognition computer vision algorithms with biological concepts. The gain are expected in the following: Recognition latency and accuracy (faster and better), less data needed to train algorithms and of decreased …