Patent ID: 11869147
Assignee: DASSAULT SYSTEMES
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method of machine-learning comprising:
obtaining an architecture for a neural network which is configured to take as an input a 2D sketch, and to output a 3D model represented by the 2D sketch, the 3D model being a parameterized 3D model defined by a set of parameters consisting of a first subset of one or more parameters and a second subset of one or more parameters, and the neural network is configured to selectively:
output a value for the set, and
take as input a value for the first subset from a user, and output a value for the second subset; and

teaching the neural network;
wherein the architecture comprises a piece of data, the neural network being configured;
to selectively output a value for the set, to produce a first value for the piece of data, to determine the value for the first subset based on said first value for the piece of data, and to further determine the value for the second subset based on said first value for the piece of data, and
to selectively take as input the value for the first subset from the user and output the value of the second subset, to produce a second value for the piece of data based on the value for the first subset, to output the value for the second subset based on the second value for the piece of data.