An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN) System capable of yielding good classification results when using both synthetic input data and real data captured from Dynamic Vision Sensor (DVS) chips. The proposed supervised m...

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Bibliographic Details
Main Authors: Evangelos Stromatias, Miguel Soto, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-06-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural networks
supervised learning
event driven processing
DVS sensors
convolutional neural networks
fully connected neural networks
Online Access:http://journal.frontiersin.org/article/10.3389/fnins.2017.00350/full

Internet

http://journal.frontiersin.org/article/10.3389/fnins.2017.00350/full

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