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We study deep neural networks for classification of images with quality distortions.
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Caltech-256 object category dataset, 2007
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
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A two-step framework for constructing blind image quality indices
A. K. Moorthy and A. C. Bovik · 2010
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Multi-column deep neural networks for image classification
D. Ciregan, U. Meier, and J. Schmidhuber · 2012
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Single-image noise level estimation for blind denoising
X. Liu, M. Tanaka, and M. Okutomi · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2014
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Why m heads are better than one: Training a diverse ensemble of deep networks
Dirty pixels: Optimizing image classification architectures for raw sensor data
S. Diamond, V. Sitzmann, S. Boyd, G. Wetzstein, and F. Heide · 2016
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Understanding how image quality affects deep neural networks
S. Dodge and L. Karam · 2016
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Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
S. Han, H. Mao, and W. J. Dally · 2016
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Deepfool: a simple and accurate method to fool deep neural networks
S.-M. Moosavi-Dezfooli, A. Fawzi, and P. Frossard · 2016
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Towards robust deep neural networks with bang
A. Rozsa, M. Gunther, and T. E. Boult · 2016
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S. Lee, S. Purushwalkam, M. Cogswell, D. Crandall, and D. Batra · 2015
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Understanding image representations by measuring their equivariance and equivalence
K. Lenc and A. Vedaldi · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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I. Vasiljevic, A. Chakrabarti, and G. Shakhnarovich · 2016
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Improving the robustness of deep neural networks via stability training
S. Zheng, Y. Song, T. Leung, and I. Goodfellow · 2016
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On classification of distorted images with deep convolutional neural networks
Y. Zhou, S. Song, and N.-M. Cheung · 2017
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