207 citations · 314 across the 11 of their papers we have counts for
13 papers
Embedded event based object detection with spiking neural network
Jonathan Courtois, Pierre-Emmanuel Novac, Edgar Lemaire +2
The complexity of event-based object detection (OD) poses considerable challenges. Spiking Neural Networks (SNNs) show promising results and pave the way for efficient event-based…
Cortex Inspired Learning to Recover Damaged Signal Modality with ReD-SOM Model
Artem Muliukov, Laurent Rodriguez, Benoit Miramond
Recent progress in the fields of AI and cognitive sciences opens up new challenges that were previously inaccessible to study. One of such modern tasks is recovering lost data of o…
Neural information coding for efficient spike-based image denoising
Andrea Castagnetti, Alain Pegatoquet, Benoît Miramond
In recent years, Deep Convolutional Neural Networks (DCNNs) have outreached the performance of classical algorithms for image restoration tasks. However most of these methods are n…
An Analytical Estimation of Spiking Neural Networks Energy Efficiency
Edgar Lemaire, Loic Cordone, Andrea Castagnetti +3
Spiking Neural Networks are a type of neural networks where neurons communicate using only spikes. They are often presented as a low-power alternative to classical neural networks,…
Object Detection with Spiking Neural Networks on Automotive Event Data
Loïc Cordone, Benoît Miramond, Philippe Thierion
Automotive embedded algorithms have very high constraints in terms of latency, accuracy and power consumption. In this work, we propose to train spiking neural networks (SNNs) dire…
A unified software/hardware scalable architecture for brain-inspired computing based on self-organizing neural models
Artem R. Muliukov, Laurent Rodriguez, Benoit Miramond +4
The field of artificial intelligence has significantly advanced over the past decades, inspired by discoveries from the fields of biology and neuroscience. The idea of this work is…