Efficient Coding

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

How to efficiently make use of time in neural computations? ⏱️
With @laurentperrinet we developed a model of spiking neuron including, in addition to synaptic weights, synaptic delays. https://t.co/eztnd5CUMn
Come see this work on Tuesday morning at #FENS2022 poster n° 547 🪩

Antoine Grimaldi, Laurent U Perrinet

Ultra-rapid visual search in natural images using active deep learning

👉🏼 Jean-Nicolas Jérémie @JnJerem
📍Poster session at #FENS2022
🎯 Ultra-rapid visual search in natural images using active deep learning.#FENSAmbassador @SocNeuro_Tweets @laurentperrinet 1/2 pic.twitter.com/ldGJMCQb4c
— Mélina Cordeau (@CordeauMelina) July 11, 2022

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

During the #CVPR2022-#NeuroVision workshop about « What can computer vision learn from visual neuroscience? », @A_Grismaldi will talk today about « Learning hetero-synaptic delays of Spiking Neurons for motion detection » shows how to learn spike motifs !https://t.co/95HGSGUOUy

Antoine Grimaldi, Laurent U Perrinet

Last updated on 2022-05-20

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