Securing deep spiking neural networks against adversarial attacks through inherent structural parameters

R El-Allami, A Marchisio, M Shafique… - … Design, Automation & …, 2021 - ieeexplore.ieee.org
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …
被引用次数：40 相关文章

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique… - arXiv preprint arXiv …, 2020 - arxiv.org
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique… - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique… - … Design, Automation and …, 2021 - uphf.hal.science
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique… - 2021 Design, Automation …, 2021 - hal.science
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …
[PDF] researchgate.net

[PDF][PDF] Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique, I Alouani - researchgate.net
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique… - … Design, Automation and …, 2021 - pure.qub.ac.uk
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique, L Alouani - 2021 - lilloa.univ-lille.fr
Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural
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[PDF][PDF] Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique, I Alouani - past.date-conference.com
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

R El-Allami, A Marchisio, M Shafique… - … Design, Automation & …, 2021 - repositum.tuwien.at
Deep Learning (DL) algorithms have gained popularity owing to their practical problem-
solving capacity. However, they suffer from a serious integrity threat, ie, their vulnerability to …