Aprovis-3-D

Antoine Grimaldi

“Ultra-fast vision using Spiking Neural Networks” (PhD position, 2020-09 / 2024-03)

  • APROVIS3D grant (ANR-19-CHR3-0008-03) at Aix-Marseille Université

  • Keywords: Vision, Spiking Neural Networks, Bio-Inspired Computer Vision

  • Thesis director: Dr. Laurent PERRINET, Institut de Neurosciences de la Timone (INT)

2026-07-07
A Robust Event-Driven Approach to Always-on Object Recognition
We propose a neuromimetic architecture able to perform always-on pattern recognition. To achieve this, we extended an existing …
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Amélie Gruel

“Design of bio-inspired spiking neural networks (spiking neurons) for event-based stereovision” (PhD position, 2020-09 / 2023-09)

Main publications

Amélie Gruel (2023). Réseaux de Neurones Impulsionnels Pour La Vision Embarquée Basée Sur Les Événements.

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2023-10-06
Learning heterogeneous delays in a layer of spiking neurons for fast motion detection
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
Learning heterogeneous delays of spiking neurons for motion detection
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Precise spiking motifs in neurobiological and neuromorphic data
Why do neurons communicate through spikes? By definition, spikes are all-or-none neural events which occur at continuous times. In …
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Precise spiking motifs in neurobiological and neuromorphic data
Learning heterogeneous delays of spiking neurons for motion detection
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Detection of precise spiking motifs using spike-time dependent weight and delay plasticity
The spiking response of a biological neuron depends on the precise timing of afferent spikes. This temporal aspect of the neuronal code …
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Learning heterogeneous delays of spiking neurons for motion detection

A resilient neural code in V1 to process natural images
On a daily basis, the primary visual cortex (V1) detects oriented elements from sensory inputs made of orientation distributions. To …
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A resilient neural code in V1 to process natural images
Decoding spiking motifs using neurons with heterogeneous delays
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Ultra-rapid visual search in natural images using active deep learning
Visual search, that is, the simultaneous localization and detection of a visual target of interest, is a vital task. Applied to the …
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Ultra-rapid visual search in natural images using active deep learning
Decoding orientation distributions from noisy observations in V1
Ultra-fast categorization of images containing animals in vivo and in computo
Ultra-fast categorization of images containing animals in vivo and in computo
From event-based computations to a bio-plausible Spiking Neural Network
We propose a neuromimetic online classifier for always-on digit recognition. To achieve this, we extend an existing event-based …
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A homeostatic gain control mechanism to improve event-driven object recognition
We propose a neuromimetic architecture able to perform pattern recognition. To achieve this, we extended the existing event-based …
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A robust bio-inspired approach to event-driven object recognition
We propose a neuromimetic architecture able to perform online pattern recognition. To achieve this, we extended the existing …
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Visual search as active inference
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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