AdverserialAttacks

Repo for collaboration on Image Perturbation and Adverserial Attacks. This is a research project that I am doing to investigate the robustness of Deep Neural Networks against the adversarial attacks.

Name		Name	Last commit message	Last commit date
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Adversarial Examples Detection in Deep Networks with Convolutional Filter.pdf		Adversarial Examples Detection in Deep Networks with Convolutional Filter.pdf
Adversarial Image Detection In Deep Neural Networks.pdf		Adversarial Image Detection In Deep Neural Networks.pdf
Deep Neural Networks are Easily Fooled.pdf		Deep Neural Networks are Easily Fooled.pdf
Detecting Adverserial Image Examples in Deep Neural Networks.pdf		Detecting Adverserial Image Examples in Deep Neural Networks.pdf
FaceClassifierTraining.ipynb		FaceClassifierTraining.ipynb
Facial Image Attributes Transformation via Conditional Recycle Generative Adversarial Networks.pdf		Facial Image Attributes Transformation via Conditional Recycle Generative Adversarial Networks.pdf
Noise-resistant Network - A Deep-learning Method for Face Recognition under Noise.pdf		Noise-resistant Network - A Deep-learning Method for Face Recognition under Noise.pdf
README.md		README.md
Universal Adversarial Perturbations.pdf		Universal Adversarial Perturbations.pdf
l0_attack.py		l0_attack.py
l2_attack.py		l2_attack.py
li_attack.py		li_attack.py
setup_cifar.py		setup_cifar.py
setup_inception.py		setup_inception.py
setup_mnist.py		setup_mnist.py
test.py		test.py
test_attack.py		test_attack.py
train_models.py		train_models.py
verify.py		verify.py

ya332/Adversarial-Attacks-Neural-Networks

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