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Convolution is conventionally defined as a linear operation on functions of one or more variables which commutes with shifts.
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
D H HUBEL and T N WIESEL · 1962
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Quantitative analysis of cat retinal ganglion cell response to visual stimuli
R.W. Rodieck · 1965
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Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
David Marr · 1982
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Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters
John G. Daugman · 1985
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The Design and Use of Steerable Filters
William T. Freeman and Edward H. Adelson · 1991
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Shiftable multiscale transforms
E.P. Simoncelli, W.T. Freeman, E.H. Adelson, and D.J. Heeger · 1992
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A complete invariant description for gray-level images by the harmonic analysis approach
Faouzi Ghorbel · 1994
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Elastica and Computer Vision
David Mumford · 1994
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Stochastic completion fields: a neural model of illusory contour shape and salience
Lance R. Williams and David W. Jacobs · 1997
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The Hankel Transform
Robert Piessens · 2000
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Characterizing the distribution of completion shapes with corners using a mixture of random processes
Karvel K. Thornber and Lance R. Williams · 2000
Cited alongside, same era.
Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape
Lance R. Williams and Karvel K. Thornber · 2001
Cited alongside, same era.
A rotation and translation invariant discrete saliency network
Lance R. Williams and John W. Zweck · 2003
Cited alongside, same era.
Euclidean Group Invariant Computation of Stochastic Completion Fields Using Shiftable-Twistable Functions
John Zweck and Lance R. Williams · 2004
Rotation Equivariant Vector Field Networks
Diego Marcos, Michele Volpi, Nikos Komodakis, and Devis Tuia · 2017
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Harmonic deep: Networks translation and rotation equivariance
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov, and Gabriel J. Brostow · 2017
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RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks
Xiuyuan Cheng, Qiang Qiu, Robert Calderbank, and Guillermo Sapiro · 2018
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Learning Steerable Filters for Rotation Equivariant CNNs
Maurice Weiler, Fred A. Hamprecht, and Martin Storath · 2018
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General E(2) - Equivariant steerable CNNs
Maurice Weiler and Gabriele Cesa · 2019
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Deep scale-spaces: equivariance over scale
Daniel E. Worrall and Max Welling · 2019
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Cited alongside, same era.
Group Equivariant Convolutional Networks
Taco S. Cohen and Max Welling · 2016
Cited alongside, same era.
Scale-equivariant steerable networks
Ivan Sosnovik, Michał Szmaja, and Arnold Smeulders · 2020
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