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Deep learning based method and apparatus for three dimensional model triangular facet feature learning and classifying

机译:基于深度学习的三维模型三角面特征学习与分类的方法和装置

摘要

The invention discloses a deep learning based method for three dimensional (3D) model triangular facet feature learning and classifying and an apparatus. The method includes: constructing a deep convolutional neural network (CNN) feature learning model; training the deep CNN feature learning model; extracting a feature from, and constructing a feature vector for, a 3D model triangular facet having no class label, and reconstructing a feature in the constructed feature vector using a bag-of-words algorithm; determining an output feature corresponding to the 3D model triangular facet having no class label according to the trained deep CNN feature learning model and an initial feature corresponding to the 3D model triangular facet having no class label; and performing classification. The method enhances the capability to describe 3D model triangular facets, thereby ensuring the accuracy of 3D model triangular facet feature learning and classifying results.
机译:本发明公开了一种基于深度学习的三维(3D)模型三角面特征学习和分类的方法及装置。该方法包括:构建深度卷积神经网络(CNN)特征学习模型;训练CNN深度学习模型;从没有类别标签的3D模型三角形刻面中提取特征并为其构建特征矢量,并使用词袋算法在所构建的特征矢量中重建特征;根据训练后的深度CNN特征学习模型,确定对应于不具有类别标签的3D模型三角形刻面的输出特征;以及确定对应于不具有类别标签的3D模型三角形刻面的初始特征;并进行分类。该方法增强了描述3D模型三角形刻面的能力,从而确保了3D模型三角形刻面特征学习和分类结果的准确性。

著录项

  • 公开/公告号US10049299B2

    专利类型

  • 公开/公告日2018-08-14

    原文格式PDF

  • 申请/专利权人 BEIHANG UNIVERSITY;

    申请/专利号US201715439896

  • 申请日2017-02-22

  • 分类号G06K9;G06K9/62;G06N3/04;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 13:05:22

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