Deep Learning

Kernel Heterogeneity Improves Sparseness of Natural Images Representations
Both biological and artificial neural networks inherently balance their performance with their operational cost, which balances their …
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Ultra-Fast Image Categorization in biology and in neural models
Humans are able to robustly categorize images and can, for instance, detect the presence of an animal in a briefly flashed image in as …
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Ultra-Fast Image Categorization in biology and in neural models
Pooling in a predictive model of V1 explains functional and structural diversity across species
Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high …
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Pooling in a predictive model of V1 explains functional and structural diversity across species
Retinotopic mapping improves the reliability of image classification
Ultra-fast categorization of images containing animals in vivo and in computo
Ultra-fast categorization of images containing animals in vivo and in computo
Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to …
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Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
Visual search as active inference
Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding
Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …
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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 …
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Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding
Cells in the primary visual cortex of mammals (V1) have historically been divided into two classes: simple and complex. Simple cells …
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Effect of top-down connections in Hierarchical Sparse Coding
Hierarchical Sparse Coding (HSC) is a powerful model to efficiently represent multi-dimensional, structured data such as images. The …
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Effect of top-down connections in Hierarchical Sparse Coding
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 …
2019-07-15
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Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system
Both neurophysiological and psychophysical experiments have pointed out the crucial role of recurrent and feedback connections to …
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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 …
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Modelling Complex Cells of Early Visual Cortex using Predictive Coding
Sparse Deep Predictive Coding to model visual object recognition
Sparse Deep Predictive Coding to model visual object recognition
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 …
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A low-cost, accessible eye tracking framework
Recording eye movements is a technique that attracts an increasing number of scientists, but also in the general public. Indeed, this …
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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 …
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On the Origins of Hierarchy in Visual Processing
It is widely assumed that visual processing follows a forward sequence of processing steps along a hierarchy of laminar sub-populations …
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Selectivity to oriented patterns of different precisions
The selectivity of the visual system to oriented patterns is very well documented in a wide range of species, especially in mammals. In …
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Selectivity to oriented patterns of different precisions
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 …
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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 …
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Efficient learning of sparse image representations using homeostatic regulation
One core advantage of sparse representations is the efficient coding of complex signals using compact codes. For instance, it allows …
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Efficient learning of sparse image representations using homeostatic regulation
One core advantage of sparse representations is the efficient coding of complex signals using compact codes. For instance, it allows …
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