Invention Grant
- Patent Title: Machine-learning for 3D modeled object inference
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Application No.: US16727035Application Date: 2019-12-26
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Publication No.: US11443192B2Publication Date: 2022-09-13
- Inventor: Eloi Mehr
- Applicant: DASSAULT SYSTEMES
- Applicant Address: FR Velizy Villacoublay
- Assignee: DASSAULT SYSTEMES
- Current Assignee: DASSAULT SYSTEMES
- Current Assignee Address: FR Velizy Villacoublay
- Agency: Oblon, McClelland, Maier & Neustadt, L.L.P.
- Priority: EP18306882 20181229
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06T7/55 ; G06T17/20 ; G06N20/00

Abstract:
The disclosure notably relates to a computer-implemented method of machine-learning. The method includes obtaining 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 includes, 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 includes 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.
Public/Granted literature
- US20200250540A1 MACHINE-LEARNING FOR 3D MODELED OBJECT INFERENCE Public/Granted day:2020-08-06
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