Efficient Coding

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 …

Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Ryad Benosman, Laurent U Perrinet

Retinotopy improves the categorisation and localisation of visual objects in CNNs

as was presented at the 32nd International Conference on Artificial Neural Networks (ICANN 2023) in Heraklion (Greece).

this proceedings paper follows up the poster presented in :
Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet (2023). Retinotopy improves the categorisation and localisation of visual objects in CNNs. In preparation.
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Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet
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Retinotopy improves the categorisation and localisation of visual objects in CNNs

Learning heterogeneous delays in a layer of spiking neurons for fast motion detection

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full code with extensive Supplementary Material
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this paper is a follow-up of
Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet (2022). Learning heterogeneous delays of spiking neurons for motion detection. Proceedings of ICIP 2022.
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Antoine Grimaldi, Laurent U Perrinet
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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 …

Jean-Nicolas Jérémie, Laurent U Perrinet

Ultra-Fast Image Categorization in biology and in neural models

Retinotopy improves the categorisation and localisation of visual objects in CNNs

as was presented at the Computational Cognitive Neuroscience Society Meeting 2023 in Oxford

see a follow-up presentation in:
Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet (2023). Retinotopy improves the categorisation and localisation of visual objects in CNNs. 32nd International Conference on Artificial Neural Networks (ICANN 2023).
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Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet
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Stakes of Neuromorphic Foveation: a promising future for embedded event cameras

Amélie Gruel, Dalia Hareb, Antoine Grimaldi, Jean Martinet, Laurent U Perrinet, Bernabé Linares-Barranco, Teresa Serrano-Gotarredona

Learning heterogeneous delays of spiking neurons for motion detection

for a follow-up, check out
Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet (2022). Learning heterogeneous delays of spiking neurons for motion detection. Proceedings of ICIP 2022.
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Antoine Grimaldi, Laurent U Perrinet
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Ultra-rapid visual search in natural images using active deep learning

This work extends to natural scenes a previous work on visual search on a simplified task formulated in
Emmanuel Daucé, Pierre Albigès, Laurent U Perrinet (2020). A dual foveal-peripheral visual processing model implements efficient saccade selection. Journal of Vision.
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Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet
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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. …

Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet

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 …

Jean-Nicolas Jérémie, Emmanuel Daucé, Laurent U Perrinet

Learning heterogeneous delays of Spiking Neurons for motion detection

for a follow-up, check out
Learning heterogeneous delays of spiking neurons for motion detection
Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet
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Antoine Grimaldi, Laurent U Perrinet

Last updated on 2022-05-20

Contributions of neuroscience to the detection and localization of objects in visual inputs

for visual search see:
A dual foveal-peripheral visual processing model implements efficient saccade selection
Emmanuel Daucé, Pierre Albigès, Laurent U Perrinet
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for retinotopy, see:
Retinotopic mapping improves the reliability of image classification
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for event-based computations, see:
Learning heterogeneous delays of Spiking Neurons for motion detection
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for event-based motion detection, see:
Learning heterogeneous delays of spiking neurons for motion detection
Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet
PDF Cite DOI Venue URL

Emmanuel Daucé, Laurent U Perrinet

Last updated on 2022-06-16

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 …

Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Ryad Benosman, Laurent U Perrinet

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 …

Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Laurent U Perrinet, Ryad Benosman

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 …

Antoine Grimaldi, Victor Boutin, Sio-Hoi Ieng, Laurent U Perrinet, Ryad Benosman