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[1] Geoffrey E. Hinton,et al. Transforming Auto-Encoders , 2011, ICANN.
[2] Remco Duits,et al. New Approximation of a Scale Space Kernel on SE(3) and Applications in Neuroimaging , 2015, SSVM.
[3] Pascal Libuschewski,et al. Group Equivariant Capsule Networks , 2018, NeurIPS.
[4] Stéphane Mallat,et al. Deep roto-translation scattering for object classification , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Remco Duits. Perceptual organization in image analysis : a mathematical approach based on scale, orientation and curvature , 2005 .
[6] Stephan J. Garbin,et al. Harmonic Networks: Deep Translation and Rotation Equivariance , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] van Ma Markus Almsick,et al. Context models of lines and contours , 2007 .
[8] Yi Li,et al. Deformable Convolutional Networks , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[9] Gabriel J. Brostow,et al. CubeNet: Equivariance to 3D Rotation and Translation , 2018, ECCV.
[10] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[11] Mitko Veta,et al. Roto-Translation Covariant Convolutional Networks for Medical Image Analysis , 2018, MICCAI.
[12] Samaneh Abbasi-Sureshjani,et al. Analysis of Vessel Connectivities in Retinal Images by Cortically Inspired Spectral Clustering , 2015, Journal of Mathematical Imaging and Vision.
[13] Koray Kavukcuoglu,et al. Exploiting Cyclic Symmetry in Convolutional Neural Networks , 2016, ICML.
[14] A. Makadia,et al. Learning SO(3) Equivariant Representations with Spherical CNNs , 2019, International Journal of Computer Vision.
[15] Devis Tuia,et al. Scale equivariance in CNNs with vector fields , 2018, ArXiv.
[16] G. Chirikjian,et al. Engineering Applications of Noncommutative Harmonic Analysis: With Emphasis on Rotation and Motion Groups , 2000 .
[17] D. Fitzpatrick,et al. Orientation Selectivity and the Arrangement of Horizontal Connections in Tree Shrew Striate Cortex , 1997, The Journal of Neuroscience.
[18] E. Franken. Enhancement of crossing elongated structures in images , 2008 .
[19] Andrea Vedaldi,et al. Warped Convolutions: Efficient Invariance to Spatial Transformations , 2016, ICML.
[20] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[21] Geoffrey E. Hinton,et al. Dynamic Routing Between Capsules , 2017, NIPS.
[22] Bernhard Burgeth,et al. Scale Spaces on Lie Groups , 2007, SSVM.
[23] Zhaoxiang Zhang,et al. Scale-Aware Trident Networks for Object Detection , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[24] Max Welling,et al. Group Equivariant Convolutional Networks , 2016, ICML.
[25] Alexander S. Ecker,et al. A rotation-equivariant convolutional neural network model of primary visual cortex , 2018, ICLR.
[26] Remco Duits,et al. A PDE Approach to Data-Driven Sub-Riemannian Geodesics in SE(2) , 2015, SIAM J. Imaging Sci..
[27] Vincent Andrearczyk,et al. Exploring local rotation invariance in 3D CNNs with steerable filters , 2018, MIDL.
[28] Taco Cohen,et al. 3D G-CNNs for Pulmonary Nodule Detection , 2018, ArXiv.
[29] Richard Kronland-Martinet,et al. A real-time algorithm for signal analysis with the help of the wavelet transform , 1989 .
[30] Max Welling,et al. 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data , 2018, NeurIPS.
[31] Pedro M. Domingos,et al. Deep Symmetry Networks , 2014, NIPS.
[32] I. Biederman. Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.
[33] Iasonas Kokkinos,et al. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Daniel E. Worrall,et al. Deep Scale-spaces: Equivariance Over Scale , 2019, NeurIPS.
[35] Xiaowei Zhou,et al. Polar Transformer Networks , 2017, ICLR.
[36] Remco Duits,et al. Training of Templates for Object Recognition in Invertible Orientation Scores: Application to Optic Nerve Head Detection in Retinal Images , 2015, EMMCVPR.
[37] Maurice Weiler,et al. Learning Steerable Filters for Rotation Equivariant CNNs , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[38] Bart M. ter Haar Romeny,et al. Fast and Accurate Gaussian Derivatives Based on B-Splines , 2007, SSVM.
[39] Maurice Weiler,et al. A General Theory of Equivariant CNNs on Homogeneous Spaces , 2018, NeurIPS.
[40] Giovanna Citti,et al. A Cortical Based Model of Perceptual Completion in the Roto-Translation Space , 2006, Journal of Mathematical Imaging and Vision.
[41] Giovanna Citti,et al. From receptive profiles to a metric model of V1 , 2018, Journal of Computational Neuroscience.
[42] Remco Duits,et al. Template Matching via Densities on the Roto-Translation Group , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[43] D. Hubel,et al. Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.
[44] Li Li,et al. Tensor Field Networks: Rotation- and Translation-Equivariant Neural Networks for 3D Point Clouds , 2018, ArXiv.
[45] Heinrich Müller,et al. SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[46] Remco Duits,et al. Optimal Paths for Variants of the 2D and 3D Reeds–Shepp Car with Applications in Image Analysis , 2016, Journal of Mathematical Imaging and Vision.
[47] Max Welling,et al. Rotation Equivariant CNNs for Digital Pathology , 2018, MICCAI.
[48] Nikos Komodakis,et al. Rotation Equivariant Vector Field Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[49] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[50] Risi Kondor,et al. On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups , 2018, ICML.
[51] Max Welling,et al. Gauge Equivariant Convolutional Networks and the Icosahedral CNN 1 , 2019 .
[52] Wolfgang Arendt,et al. Integral representations of resolvents and semigroups , 1994 .
[53] Remco Duits,et al. Crossing-Preserving Coherence-Enhancing Diffusion on Invertible Orientation Scores , 2009, International Journal of Computer Vision.
[54] Marco Reisert,et al. Spherical Tensor Algebra: A Toolkit for 3D Image Processing , 2017, Journal of Mathematical Imaging and Vision.
[55] Qiang Qiu,et al. Oriented Response Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Remco Duits,et al. Association Fields via Cuspless Sub-Riemannian Geodesics in SE(2) , 2013, Journal of Mathematical Imaging and Vision.
[57] Peter Bailis,et al. Equivariant Transformer Networks , 2019, ICML.
[58] E. Baspinar. Minimal Surfaces in Sub-Riemannian Structures and Functional Geometry of the Visual Cortex , 2018 .
[59] Lawrence D. Jackel,et al. Handwritten Digit Recognition with a Back-Propagation Network , 1989, NIPS.
[60] Max Welling,et al. Spherical CNNs , 2018, ICLR.
[61] Kostas Daniilidis,et al. 3D object classification and retrieval with Spherical CNNs , 2017, ArXiv.
[62] J. Petitot. The neurogeometry of pinwheels as a sub-Riemannian contact structure , 2003, Journal of Physiology-Paris.