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- Title
基于卷积神经网络的三维CAD模型分类.
- Authors
丁博; 伊明
- Abstract
Due to the intrinsic complexity of 3D CAD models,the automatic model classification methods are scarce. In this paper,an automatic 3D CAD model classification approach based on Convolutional Neural Network( CNN) is proposed. At first,in order to obtain 2D views along the fixed angle,we adopt the sphere to wrap the 3D CAD model entirely,then the typical views are selected from the 2D views based on Apriori,and then preprocessed as input vectors for category recognition. Parameter adjustment based on AlexNet model,a novel CNN classifier for 3D CAD models is constructed. Finally,forward propagation and back propagation are selected to train the convolutional neural network to improve its generalization performance. Experiments show that this method can improve the accuracy and efficiency of model classification.
- Subjects
ARTIFICIAL neural networks; BACK propagation; AUTOMATIC classification; GENERALIZATION; SPHERES
- Publication
Journal of Harbin University of Science & Technology, 2020, Vol 25, Issue 1, p66
- ISSN
1007-2683
- Publication type
Article
- DOI
10.15938/j.jhust.2020.01.010