A GPU-Based Framework for Generating Implicit Datasets of Voxelized Polygonal Models for the Training of 3D Convolutional Neural Networks

A GPU-Based Framework for Generating Implicit Datasets of Voxelized Polygonal Models for the Training of 3D Convolutional Neural Networks

In this paper we present an efficient GPU-based framework to dynamically perform the voxelization of polygonal models for training 3D convolutional neural networks. It is designed to manage the dataset augmentation by using efficient geometric transformations and random vertex displacements in GPU....

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Bibliographic Details
Main Authors: Carlos J. Ogayar-Anguita, Antonio J. Rueda-Ruiz, Rafael J. Segura-Sanchez, Miguel Diaz-Medina, Angel L. Garcia-Fernandez
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Voxelization
B-rep
boundary representation
polygonal meshes
convolutional neural network
3D-CNN
Online Access:https://ieeexplore.ieee.org/document/8955843/

Internet

https://ieeexplore.ieee.org/document/8955843/

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