63 citations · 207 across the 17 of their papers we have counts for
17 papers
Frozen Backpropagation: Relaxing Weight Symmetry in Deep Spiking Neural Networks
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware can greatly reduce energy costs compared to GPU-based training. However, implementing Backpropagation (BP…
Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Spike Timing-Dependent Plasticity (STDP) is a promising substitute to backpropagation for local training of Spiking Neural Networks (SNNs) on neuromorphic hardware. STDP allows SNN…
SnatchML: Hijacking ML models without Training Access
Mahmoud Ghorbel, Halima Bouzidi, Ioan Marius Bilasco +1
Model hijacking can cause significant accountability and security risks since the owner of a hijacked model can be framed for having their model offer illegal or unethical services…
eMotion-GAN: A Motion-based GAN for Photorealistic and Facial Expression Preserving Frontal View Synthesis
Omar Ikne, Benjamin Allaert, Ioan Marius Bilasco +1
Many existing facial expression recognition (FER) systems encounter substantial performance degradation when faced with variations in head pose. Numerous frontalization methods hav…
S3TC: Spiking Separated Spatial and Temporal Convolutions with Unsupervised STDP-based Learning for Action Recognition
Mireille El-Assal, Pierre Tirilly, Ioan Marius Bilasco
Video analysis is a major computer vision task that has received a lot of attention in recent years. The current state-of-the-art performance for video analysis is achieved with De…
Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks
Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware has the potential to significantly reduce the energy consumption of artificial neural network training. S…
Spiking Two-Stream Methods with Unsupervised STDP-based Learning for Action Recognition
Mireille El-Assal, Pierre Tirilly, Ioan Marius Bilasco
Video analysis is a computer vision task that is useful for many applications like surveillance, human-machine interaction, and autonomous vehicles. Deep Convolutional Neural Netwo…
AdvART: Adversarial Art for Camouflaged Object Detection Attacks
Amira Guesmi, Ioan Marius Bilasco, Muhammad Shafique +1
Physical adversarial attacks pose a significant practical threat as it deceives deep learning systems operating in the real world by producing prominent and maliciously designed ph…
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…
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…
Dynamic Facial Expression Recognition under Partial Occlusion with Optical Flow Reconstruction
Delphine Poux, Benjamin Allaert, Nacim Ihaddadene +3
Video facial expression recognition is useful for many applications and received much interest lately. Although some solutions give really good results in a controlled environment…
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…
Impact of facial landmark localization on facial expression recognition
Romain Belmonte, Benjamin Allaert, Pierre Tirilly +3
Although facial landmark localization (FLL) approaches are becoming increasingly accurate for characterizing facial regions, one question remains unanswered: what is the impact of…
Facial Expressions Analysis Under Occlusions Based on Specificities of Facial Motion Propagation
Delphine Poux, Benjamin Allaert, Jose Mennesson +3
Although much progress has been made in the facial expression analysis field, facial occlusions are still challenging. The main innovation brought by this contribution consists in…
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…
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…
Advanced local motion patterns for macro and micro facial expression recognition
B. Allaert, IM. Bilasco, C. Djeraba
In this paper, we develop a new method that recognizes facial expressions, on the basis of an innovative local motion patterns feature, with three main contributions. The first one…