Title:
３Ｄモデル化オブジェクト推定のための機械学習
Document Type and Number:
Japanese Patent JP7464387
Kind Code:
B2
Abstract:
The invention notably relates to a computer-implemented method of machine-learning. The method comprises providing a dataset including 3D modeled objects which each represent a respective mechanical part. The dataset has one or more sub-datasets. Each sub-dataset forms at least a part of the dataset. The method further comprises, for each respective sub-dataset, determining a base template and learning a neural network configured for inference of deformations of the base template each into a respective 3D modeled object. The base template is a 3D modeled object which represents a centroid of the 3D modeled objects of the sub-dataset. The learning comprises a training based on the sub-dataset. This constitutes an improved method of machine-learning with a dataset including 3D modeled objects which each represent a respective mechanical part.
Inventors:
erotic mail
Application Number:
JP2019232006A
Publication Date:
April 09, 2024
Filing Date:
December 23, 2019
Export Citation:
Assignee:
DASSAULT SYSTEMES
International Classes:
G06F30/27; G06F30/10; G06F30/12; G06T17/20
Domestic Patent References:
| JP5081356A |
Foreign References:
| CN108959787A | ||||
| US20170372480 |
Other References:
山田亮 ほか,形状に対する感性の獲得/分類実験とその利用について,電気学会研究会資料 ,日本,社団法人電気学会,2000年01月27日,IIS-00-1~12,pages 1-6
Attorney, Agent or Firm:
Asahi Patent Office