activity
20192022
most citedA Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP

7 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2022

2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition

Mireille El-Assal, Pierre Tirilly, Ioan Marius Bilasco

Current advances in technology have highlighted the importance of video analysis in the domain of computer vision. However, video analysis has considerably high computational costs…

cs.CV20217 cited

A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP

El-Assal Mireille, Tirilly Pierre, Bilasco Ioan Marius

There has been an increasing interest in spiking neural networks in recent years. SNNs are seen as hypothetical solutions for the bottlenecks of ANNs in pattern recognition, such a…

cs.CV2020

Improving STDP-based Visual Feature Learning with Whitening

Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco

In recent years, spiking neural networks (SNNs) emerge as an alternative to deep neural networks (DNNs). SNNs present a higher computational efficiency using low-power neuromorphic…

cs.CV2019

Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP

Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco +2

Spiking neural networks (SNNs) are good candidates to produce ultra-energy-efficient hardware. However, the performance of these models is currently behind traditional methods. Int…

cs.CV2019

Unsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?

Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco +2

Spiking neural networks (SNNs) equipped with latency coding and spike-timing dependent plasticity rules offer an alternative to solve the data and energy bottlenecks of standard co…