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The effectiveness of Convolutional Neural Networks stems in large part from their ability to exploit the translation invariance that is inherent in many learning problems.
Sampling and reconstruction of wave-number-limited functions in n-dimensional euclidean spaces
Daniel P Petersen and David Middleton · 1962
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The processing of hexagonally sampled two-dimensional signals
Russel M Mersereau · 1979
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A hexagonal pyramid data structure for image processing
N Peri Hartman and Steven L Tanimoto · 1984
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Object recognition from local scale-invariant features
David G Lowe · 1999
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The art of data augmentation
David A Van Dyk and Xiao-Li Meng · 2001
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Histograms of oriented gradients for human detection
Navneet Dalal and Bill Triggs · 2005
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Hexagonal image processing: A practical approach
Lee Middleton and Jayanthi Sivaswamy · 2006
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Quasi-interpolating spline models for hexagonally-sampled data
Laurent Condat and Dimitri Van De Ville · 2007
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A novel set of rotationally and translationally invariant features for images based on the non-commutative bispectrum
Risi Kondor · 2007
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Deep symmetry networks
Robert Gens and Pedro M Domingos · 2014
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Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
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Group equivariant convolutional networks
Taco S Cohen and Max Welling · 2016
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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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Harmonic networks: Deep translation and rotation equivariance
Daniel E Worrall, Stephan J Garbin, Daniyar Turmukhambetov, and Gabriel J Brostow · 2016
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Steerable cnn
Taco S Cohen and Max Welling · 2017
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Carlos Esteves, Christine Allen-Blanchette, Xiaowei Zhou, and Kostas Daniilidis · 2017
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Deep rotation equivariant network
Junying Li, Zichen Yang, Haifeng Liu, and Deng Cai · 2017
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Equivariance through parameter-sharing
Siamak Ravanbakhsh, Jeff Schneider, and Barnabas Poczos · 2017
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Warped convolutions: Efficient invariance to spatial transformations
João F Henriques and Andrea Vedaldi · 2016
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Rotation equivariant vector field networks
Diego Marcos, Michele Volpi, Nikos Komodakis, and Devis Tuia · 2016
Cited alongside, same era.
Aid: A benchmark data set for performance evaluation of aerial scene classification
Gui-Song Xia, Jingwen Hu, Fan Hu, Baoguang Shi, Xiang Bai, Yanfei Zhong, Liangpei Zhang, and Xiaoqiang Lu · 2017
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Yanzhao Zhou, Qixiang Ye, Qiang Qiu, and Jianbin Jiao · 2017
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