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Thanks to the use of convolution and pooling layers, convolutional neural networks were for a long time thought to be shift-invariant.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
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Shift invariance and the neocognitron
Etienne Barnard and David Casasent · 1990
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Handwritten digit recognition with a back-propagation network
Yann LeCun, Bernhard E. Boser, John S. Denker, Donnie Henderson, R. E. Howard, Wayne E. Hubbard, and Lawrence D. Jackel · 1990
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Shiftable multiscale transforms
Eero P Simoncelli, William T Freeman, Edward H Adelson, and David J Heeger · 1992
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Gradient-based learning applied to document recognition
Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Discrete-time signal processing. Vol. 2
Alan V Oppenheim, John R Buck, and Ronald W Schafer · 2001
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Neocognitron for handwritten digit recognition
Kunihiko Fukushima · 2003
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Measuring invariances in deep networks
Ian Goodfellow, Honglak Lee, Quoc V. Le, Andrew Saxe, and Andrew Y. Ng · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Deep learners benefit more from out-of-distribution examples
Yoshua Bengio, Frédéric Bastien, Arnaud Bergeron, Nicolas Boulanger–Lewandowski, Thomas Breuel, Youssouf Chherawala, Moustapha Cisse, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain Pannetier Lebeuf, Razvan Pascanu, Salah Rifai, François Savard, and Guillaume Sicard · 2011
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Group invariant scattering
Stéphane Mallat · 2012
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Invariant scattering convolution networks
J. Bruna and S. Mallat · 2013
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Rotation, scaling and deformation invariant scattering for texture discrimination
Laurent Sifre and Stephane Mallat · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Semantic image segmentation with deep convolutional nets and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2014
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Locally scale-invariant convolutional neural networks
Angjoo Kanazawa, Abhishek Sharma, and David W. Jacobs · 2014
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Convolutional kernel networks
Julien Mairal, Piotr Koniusz, Zaid Harchaoui, and Cordelia Schmid · 2014
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Scale-invariant convolutional neural networks
Yichong Xu, Tianjun Xiao, Jiaxing Zhang, Kuiyuan Yang, and Zheng Zhang · 2014
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Manitest: Are classifiers really invariant?
Alhussein Fawzi and Pascal Frossard · 2015
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Explaining and harnessing adversarial examples
Ian Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Deep image: Scaling up image recognition
Ren Wu, Shengen Yan, Yi Shan, Qingqing Dang, and Gang Sun · 2015
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Learning rotation-invariant convolutional neural networks for object detection in vhr optical remote sensing images
G. Cheng, P. Zhou, and J. Han · 2016
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Group equivariant convolutional networks
Taco Cohen and Max Welling · 2016
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
L. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2018
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Generalisation in humans and deep neural networks
Robert Geirhos, Carlos R. M. Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, and Felix A. Wichmann · 2018
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Geometric robustness of deep networks: Analysis and improvement
Can Kanbak, Seyed-Mohsen Moosavi-Dezfooli, and Pascal Frossard · 2018
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
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Pooling is neither necessary nor sufficient for appropriate deformation stability in cnns
Avraham Ruderman, Neil C Rabinowitz, Ari S Morcos, and Daniel Zoran · 2018
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Exploiting cyclic symmetry in convolutional neural networks
Sander Dieleman, Jeffrey De Fauw, and Koray Kavukcuoglu · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Examining the impact of blur on recognition by convolutional networks
Igor Vasiljevic, Ayan Chakrabarti, and Gregory Shakhnarovich · 2016
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Invariance and stability of deep convolutional representations
Alberto Bietti and Julien Mairal · 2017
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
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Learning steerable filters for rotation equivariant cnns
Maurice Weiler, Fred A. Hamprecht, and Martin Storath · 2018
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Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay and Yair Weiss · 2019
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Group invariance, stability to deformations, and complexity of deep convolutional representations
Alberto Bietti and Julien Mairal · 2019
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Autoaugment: Learning augmentation strategies from data
Ekin D. Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V. Le · 2019
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Exploring the landscape of spatial robustness
Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, and Aleksander Madry · 2019
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 2019
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Ganesh Sundaramoorthi and Timothy E Wang · 2019
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Making convolutional networks shift-invariant again
Richard Zhang · 2019
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Mind the pad–cnns can develop blind spots
Bilal Alsallakh, Narine Kokhlikyan, Vivek Miglani, Jun Yuan, and Orion Reblitz-Richardson · 2020
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Augmix: A simple method to improve robustness and uncertainty under data shift
Dan Hendrycks*, Norman Mu*, Ekin Dogus Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan · 2020
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How much position information do convolutional neural networks encode?
Md Amirul Islam*, Sen Jia*, and Neil D. B. Bruce · 2020
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On translation invariance in cnns: Convolutional layers can exploit absolute spatial location
Osman Semih Kayhan and Jan C. van Gemert · 2020
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Shift equivariance in object detection
Marco Manfredi and Yu Wang · 2020
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Delving deeper into anti-aliasing in convnets
Xueyan Zou, Fanyi Xiao, Zhiding Yu, and Yong Jae Lee · 2020
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