Add to ORKGNational audienceThe process of segmenting images is one of the most critical ones in automatic image analysis whose goal can be regarded as to find what objects are presented in images. Artificial neural networks have been well developed. First two generations of neural networks have a lot of successful applications. Spiking Neuron Networks (SNNs) are often referred to as the 3rd generation of neural networks which have potential to solve problems related to biological stimuli. They derive their strength and interest from an accurate modeling of synaptic interactions between neurons, taking into account the time of spike emission. SNNs overcome the computational power of neural networks made of threshold or sigmoidal units. Based on dynami...
International audienceSpiking Neuron Networks (SNNs) are often referred to as the 3rd generation ofn...
Recently, researchers have shown an increased interest in more biologically realistic neural network...
Over the past years Spiking Neural Networks (SNNs) models became attractive as a possible bridge to ...
National audienceThe process of segmenting images is one of the most critical ones in automatic imag...
National audienceThe process of segmenting images is one of the most critical ones in automatic imag...
International audienceThe process of segmenting images is one of the most critical ones in automatic...
International audienceArtificial neural networks have been well developed so far. First two generati...
A Biological Neural Network or simply BNN is an artificial abstract model of different parts of the...
International audienceSpiking Neuron Networks (SNNs) overcome the computational power of neural netw...
Neurological research shows that the biological neurons store information in the timing of spikes. S...
The spiking neural networks (SNNs) use event-driven signals to encipher physical data for neural com...
Artificial neural networks have been used as a powerful processing tool in various areas such as pat...
International audienceNumerous neural network hardware implementations now use digital reconfigurabl...
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommo...
Spiking neuron network (SNN) attaches much attention to researchers in neuromorphic engineering and ...
International audienceSpiking Neuron Networks (SNNs) are often referred to as the 3rd generation ofn...
Recently, researchers have shown an increased interest in more biologically realistic neural network...
Over the past years Spiking Neural Networks (SNNs) models became attractive as a possible bridge to ...
National audienceThe process of segmenting images is one of the most critical ones in automatic imag...
National audienceThe process of segmenting images is one of the most critical ones in automatic imag...
International audienceThe process of segmenting images is one of the most critical ones in automatic...
International audienceArtificial neural networks have been well developed so far. First two generati...
A Biological Neural Network or simply BNN is an artificial abstract model of different parts of the...
International audienceSpiking Neuron Networks (SNNs) overcome the computational power of neural netw...
Neurological research shows that the biological neurons store information in the timing of spikes. S...
The spiking neural networks (SNNs) use event-driven signals to encipher physical data for neural com...
Artificial neural networks have been used as a powerful processing tool in various areas such as pat...
International audienceNumerous neural network hardware implementations now use digital reconfigurabl...
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommo...
Spiking neuron network (SNN) attaches much attention to researchers in neuromorphic engineering and ...
International audienceSpiking Neuron Networks (SNNs) are often referred to as the 3rd generation ofn...
Recently, researchers have shown an increased interest in more biologically realistic neural network...
Over the past years Spiking Neural Networks (SNNs) models became attractive as a possible bridge to ...