Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

Over the past few years, Spiking Neural Networks (SNNs) have become popular as a possible pathway to enable low-power event-driven neuromorphic hardware. However, their application in machine learning have largely been limited to very shallow neural network architectures for simple problems. In this...

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Bibliographic Details
Main Authors: Abhronil Sengupta, Yuting Ye, Robert Wang, Chiao Liu, Kaushik Roy
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-03-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural networks
event-driven neural networks
sparsity
neuromorphic computing
visual recognition
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00095/full

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