Invention Grant
- Patent Title: Learning a neural network for inference of solid CAD features
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Application No.: US16727413Application Date: 2019-12-26
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Publication No.: US11922573B2Publication Date: 2024-03-05
- Inventor: Fernando Manuel Sanchez Bermudez , 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: EP 306886 2018.12.29
- Main IPC: G06T17/10
- IPC: G06T17/10 ; G06F30/23 ; G06F30/27 ; G06N3/084 ; G06N3/088 ; G06N5/046 ; G06N20/10 ; G06T17/20 ; G06V10/44 ; G06V10/764 ; G06V10/82 ; G06V20/64 ; G06F119/18

Abstract:
The disclosure notably relates to computer-implemented method for learning a neural network configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes providing a dataset including freehand drawings each representing a respective 3D shape, and learning the neural network based on the dataset. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape.
Public/Granted literature
- US20200210845A1 LEARNING A NEURAL NETWORK FOR INFERENCE OF SOLID CAD FEATURES Public/Granted day:2020-07-02
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