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Deep neural networks provide unprecedented performance in all image classification problems, taking advantage of huge amounts of data available for training.
Image quality assessment: from error visibility to structural similarity,
Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, · 2004
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Image information and visual quality,
H. R. Sheikh, A. C. Bovik, · 2006
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Exact histogram specification optimized for structural similarity,
A. Avanaki, · 2008
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Imagenet classification with deep convolutional neural networks,
A. Krizhevsky, I. Sutskever, G. Hinton, · 2012
Earlier work this paper cites.
No-reference image quality assessment in the spatial domain,
A. Mittal, A. K. Moorthy, A. C. Bovik, · 2012
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Intriguing properties of neural networks,
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, R. Fergus, · 2014
Earlier work this paper cites.
Explaining and harnessing adversarial examples,
I. Goodfellow, J. Shlens, C. Szegedy, · 2015
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Blind image quality evaluation using perception based features,
N. Venkatanath, D. Praneeth, M. C. Bh, S. S. Channappayya, S. S. Medasani, · 2015
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Adversarial examples in the physical world,
A. Kurakin, I. Goodfellow, S. Bengio, · 2016
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Transferability in machine learning: from phenomena to black-box attacks using adversarial samples,
N. Papernot, P. McDaniel, I. Goodfellow, · 2016
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Adversarial diversity and hard positive generation,
A. Rozsa, E. M. Rudd, T. E. Boult, · 2016
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Deep residual learning for image recognition,
K. He, X. Zhang, S. Ren, J. Sun, · 2016
Cited alongside, same era.
Towards evaluating the robustness of neural networks,
N. Carlini, D. Wagner, · 2017
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks,
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, A. Vladu, · 2017
Cited alongside, same era.
Houdini: Fooling deep structured prediction models,
M. Cisse, Y. Adi, N. Neverova, J. Keshet, · 2017
Cited alongside, same era.
Practical black-box attacks against machine learning,
N. Papernot, P. McDaniel, I. Goodfellow, S. Jha, Z. B. Celik, A. Swami, · 2017
Cited alongside, same era.
On the vulnerability of deep learning to adversarial attacks for camera model identification,
F. Marra, D. Gragnaniello, L. Verdoliva, · 2018
Later among the works it cites.
AutoZOOM github repository, https://github.com/IBM/Autozoom-Attack , 2018
2018
Later among the works it cites.
Query limited black-box attack github repository, https://github.com/labsix/limited-blackbox-attacks , 2018
2018
Later among the works it cites.
Results of the CODALAB MCS2018 competition, https://competitions.codalab.org/competitions/19090#results , 2018
2018
Later among the works it cites.
Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks,
C.-C. Tu, P. Ting, P.-Y. Chen, S. Liu, H. Zhang, J. Yi, C.-J. Hsieh, S.-M. Cheng, · 2019
Closest in time.
One pixel attack for fooling deep neural networks,
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P.-Y. Chen, H. Zhang, Y. Sharma, J. Yi, C.-J. Hsieh, · 2017
Cited alongside, same era.
Simple black-box adversarial perturbations for deep networks,
N. Narodytska, S. Kasiviswanathan, · 2017
Cited alongside, same era.
Exploring the space of black-box attacks on deep neural networks,
A. Bhagoji, W. He, B. Li, D. Song, · 2017
Cited alongside, same era.
Ifg github repository, https://github.com/sunblaze-ucb/blackbox-attacks , 2017
2017
Cited alongside, same era.
Black-box adversarial attacks with limited queries and information,
A. Ilyas, L. Engstrom, A. Athalye, J. Lin, · 2018
Cited alongside, same era.
SHIELD: Fast, practical defense and vaccination for deep learning using JPEG compression,
N. Das, M. Shanbhogue, S. Chen, F. Hohman, S. Li, L. Chen, M. Kounavis, D. Chau, · 2018
Cited alongside, same era.
J. Su, D. V. Vargas, K. Sakurai, · 2019
Closest in time.
Attacking convolutional neural network using differential evolution,
J. Su, D. Vargas, K. Sakurai, · 2019
Closest in time.
Nattack: Learning the distributions of adversarial examples for an improved black-box attack on deep neural networks,
Y. Li, L. Li, L. Wang, T. Zhang, B. Gong, · 2019
Closest in time.
Y. Duan, Z. Zhao, L. Bu, F. Song, · 2019
Closest in time.
PQP github repository, https://github.com/dgragnaniello/PQP , 2019
2019
Closest in time.