Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Bilasco, Ioan"'
Spike Timing-Dependent Plasticity (STDP) is a promising substitute to backpropagation for local training of Spiking Neural Networks (SNNs) on neuromorphic hardware. STDP allows SNNs to address classification tasks by combining unsupervised STDP for f
Externí odkaz:
http://arxiv.org/abs/2410.17066
The massive deployment of Machine Learning (ML) models has been accompanied by the emergence of several attacks that threaten their trustworthiness and raise ethical and societal concerns such as invasion of privacy, discrimination risks, and lack of
Externí odkaz:
http://arxiv.org/abs/2406.01708
Many existing facial expression recognition (FER) systems encounter substantial performance degradation when faced with variations in head pose. Numerous frontalization methods have been proposed to enhance these systems' performance under such condi
Externí odkaz:
http://arxiv.org/abs/2404.09940
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 Deep Neural Networks (DNNs) that have high computational costs and need
Externí odkaz:
http://arxiv.org/abs/2309.12761
Publikováno v:
Front. Neurosci. 18 (2024)
Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware has the potential to significantly reduce the energy consumption of artificial neural network training. SNNs trained with Spike Timing-Dependent Plasticity (STDP) benefit from
Externí odkaz:
http://arxiv.org/abs/2308.02194
Video analysis is a computer vision task that is useful for many applications like surveillance, human-machine interaction, and autonomous vehicles. Deep Convolutional Neural Networks (CNNs) are currently the state-of-the-art methods for video analys
Externí odkaz:
http://arxiv.org/abs/2306.13783
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 physical perturbations. Emphasizing the evaluation of naturalness is cru
Externí odkaz:
http://arxiv.org/abs/2303.01734
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 with traditional artificial neural networks (ANNs). Spiking neural ne
Externí odkaz:
http://arxiv.org/abs/2205.13474
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 as energy efficiency. But current methods such as ANN-to-SNN conversion
Externí odkaz:
http://arxiv.org/abs/2105.14740
Autor:
Poux, Delphine, Allaert, Benjamin, Ihaddadene, Nacim, Bilasco, Ioan Marius, Djeraba, Chaabane, Bennamoun, Mohammed
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 (no occlusion), recognition in the presence of partial facial occlusio
Externí odkaz:
http://arxiv.org/abs/2012.13217