Learning Shapes on Image Sampled Points with Dynamic Graph CNNs

Castorena, Juan Enrique; Oyen, Diane Adele

doi:10.1109/SSIAI49293.2020.9094594

Title: Learning Shapes on Image Sampled Points with Dynamic Graph CNNs

Conference · Sun Jun 07 00:00:00 EDT 2020

DOI:https://doi.org/10.1109/SSIAI49293.2020.9094594· OSTI ID:1632671

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Los Alamos National Laboratory

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program

DOE Contract Number:: 89233218CNA000001

OSTI ID:: 1632671

Report Number(s):: LA-UR-20-24122

Resource Relation:: Conference: IEEE SSIAI 2020 ; 2020-03-29 - 2020-03-29 ;

Country of Publication:: United States

Language:: English

References (10)

Dynamic Graph CNN for Learning on Point Clouds Wang, Yue; Sun, Yongbin; Liu, Ziwei ACM Transactions on Graphics, Vol. 38, Issue 5 https://doi.org/10.1145/3326362	journal	October 2019
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Charles, R. Qi; Su, Hao; Kaichun, Mo 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR.2017.16	conference	July 2017
Learning the Geometric Structure of Manifolds with Singularities Using the Tensor Voting Graph Deutsch, Shay; Medioni, Gérard Journal of Mathematical Imaging and Vision, Vol. 57, Issue 3 https://doi.org/10.1007/s10851-016-0684-2	journal	October 2016
Generalizing the Hough transform to detect arbitrary shapes Ballard, D. H. Pattern Recognition, Vol. 13, Issue 2 https://doi.org/10.1016/0031-3203(81)90009-1	journal	January 1981
Geometric Deep Learning: Going beyond Euclidean data Bronstein, Michael M.; Bruna, Joan; LeCun, Yann IEEE Signal Processing Magazine, Vol. 34, Issue 4 https://doi.org/10.1109/MSP.2017.2693418	journal	July 2017
Diffusion maps Coifman, Ronald R.; Lafon, Stéphane Applied and Computational Harmonic Analysis, Vol. 21, Issue 1 https://doi.org/10.1016/j.acha.2006.04.006	journal	July 2006
Geodesic Convolutional Neural Networks on Riemannian Manifolds Masci, Jonathan; Boscaini, Davide; Bronstein, Michael M. 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) https://doi.org/10.1109/ICCVW.2015.112	conference	December 2015
Gradient-based learning applied to document recognition Lecun, Y.; Bottou, L.; Bengio, Y. Proceedings of the IEEE, Vol. 86, Issue 11 https://doi.org/10.1109/5.726791	journal	January 1998
Deep learning LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey Nature, Vol. 521, Issue 7553 https://doi.org/10.1038/nature14539	journal	May 2015
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs Monti, Federico; Boscaini, Davide; Masci, Jonathan 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR.2017.576	conference	July 2017

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