Event-Based Vision

Event cameras asynchronously report brightness changes with a temporal resolution in the order of microseconds, which makes them …

We propose a neuromimetic architecture able to perform always-on pattern recognition. To achieve this, we extended an existing …

The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …

How to efficiently make use of time in neural computations? ⏱️ With @laurentperrinet we developed a model of spiking neuron including, in addition to synaptic weights, synaptic delays. https://t.co/eztnd5CUMn Come see this work on Tuesday morning at #FENS2022 poster n° 547 🪩

The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …

During the #CVPR2022-#NeuroVision workshop about « What can computer vision learn from visual neuroscience? », @A_Grismaldi will talk today about « Learning hetero-synaptic delays of Spiking Neurons for motion detection » shows how to learn spike motifs !

for visual search see: Emmanuel Dauce, Pierre Albigès, Laurent U Perrinet (2020). A dual foveal-peripheral visual processing model implements efficient saccade selection. Journal of Vision. Preprint PDF Cite Code DOI for retinotopy, see: Jean-Nicolas Jeremie, Emmanuel Dauce, Laurent U Perrinet (2022).

Follow this future presentations Antoine Grimaldi, Laurent U Perrinet (2022). Learning heterogeneous delays of Spiking Neurons for motion detection. NeuroVision Workshop in conjunction with CVPR 2022. PDF Cite URL Glad to meet the @centuri_ls crowd at the #CENTURIday !

We propose a neuromimetic online classifier for always-on digit recognition. To achieve this, we extend an existing event-based …

We propose a neuromimetic architecture able to perform pattern recognition. To achieve this, we extended the existing event-based …

We propose a neuromimetic architecture able to perform online pattern recognition. To achieve this, we extended the existing …