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OCTREE-BASED CONVOLUTIONAL NEURAL NETWORK

机译:基于十进制的卷积神经网络

摘要

The implementations of the subject matter described herein relate to an octree-based convolutional neural network. In some implementations, there is provided a computer-implemented method for processing a three-dimensional shape. The method comprises obtaining an octree for representing the three-dimensional shape. Nodes of the octree include empty nodes and non-empty nodes. The empty nodes exclude the three-dimensional shape and are leaf nodes of the octree, and the non-empty nodes include at least a part of the three-dimensional shape. The method further comprises for nodes in the octree with a depth associated with a convolutional layer of a convolutional neural network, performing a convolutional operation of the convolutional layer to obtain an output of the convolutional layer.
机译:本文所述主题的实施方式涉及基于八叉树的卷积神经网络。在一些实施方式中,提供了一种用于处理三维形状的计算机实现的方法。该方法包括获得用于表示三维形状的八叉树。八叉树的节点包括空节点和非空节点。空节点不包括三维形状,并且是八叉树的叶节点,并且非空节点包括三维形状的至少一部分。该方法还包括:对于八叉树中具有与卷积神经网络的卷积层相关联的深度的节点,执行卷积层的卷积操作以获得卷积层的输出。

著录项

  • 公开/公告号US2020042863A1

    专利类型

  • 公开/公告日2020-02-06

    原文格式PDF

  • 申请/专利权人 MICROSOFT TECHNOLOGY LICENSING LLC;

    申请/专利号US201816606653

  • 发明设计人 PENGSHUAI WANG;YANG LIU;XIN TONG;

    申请日2018-04-20

  • 分类号G06N3/04;G06F17/15;G06F16/901;G06F1/20;

  • 国家 US

  • 入库时间 2022-08-21 11:19:00

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