A Comparative Study on the Performance and Security Evaluation of Spiking Neural Networks

A Comparative Study on the Performance and Security Evaluation of Spiking Neural Networks

The brain-inspired Spiking neural networks (SNN) claim to present advantages for visual classification tasks in terms of energy efficiency and inherent robustness. In this work, we explore the impact on network inter-layer sparsity through neural coding schemes and the intrinsic structural parameter...

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Bibliographic Details
Main Authors: Yanjie Li, Xiaoxin Cui, Yihao Zhou, Ying Li
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Spiking neural network
accuracy
energy efficiency
adversarial robustness
sparsity
Online Access:https://ieeexplore.ieee.org/document/9940625/

Internet

https://ieeexplore.ieee.org/document/9940625/

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