Qusecnets: Quantization-based defense mechanism for securing deep neural network against adversarial attacks

F Khalid, H Ali, H Tariq, MA Hanif… - 2019 IEEE 25th …, 2019 - ieeexplore.ieee.org
Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …
被引用次数：45 相关文章

[引用][C] QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, MA Hanif… - 2019 IEEE 25th …, 2019 - repositum.tuwien.at
reposiTUm: QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural
Network against Adversarial Attacks reposiTUm ABOUT REPOSITUM HELP Login News …

[引用][C] QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, MA Hanif, S Rehman… - 2019 IEEE 25th …, 2019 - cir.nii.ac.jp
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network
against Adversarial Attacks | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] …
[PDF] researchgate.net

[PDF][PDF] QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

H Ali, H Tariq, MA Hanif, F Khalid, S Rehman, R Ahmed… - researchgate.net
Deep Neural Networks (DNNs) have recently been shown vulnerable to adversarial attacks
in which the input examples are perturbed to fool these DNNs towards confidence reduction …

QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, MA Hanif, S Rehman… - arXiv preprint arXiv …, 2018 - arxiv.org
Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …

QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, M Abdullah Hanif… - arXiv e …, 2018 - ui.adsabs.harvard.edu
Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …

QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, MA Hanif… - … Symposium on On …, 2019 - nyuscholars.nyu.edu
Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …
[PDF] academia.edu

[PDF][PDF] QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, MA Hanif, S Rehman, R Ahmed… - academia.edu
Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …
[PDF] academia.edu

[PDF][PDF] QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

F Khalid, H Ali, H Tariq, MA Hanif, S Rehman, R Ahmed… - academia.edu
Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …
[PDF] researchgate.net

[PDF][PDF] QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

H Ali, H Tariq, MA Hanif, F Khalid, S Rehman, R Ahmed… - researchgate.net
Deep Neural Networks (DNNs) have recently been shown vulnerable to adversarial attacks
in which the input examples are perturbed to fool these DNNs towards confidence reduction …