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

Claim 14:
15. A device comprising:
a processor; and
a non-transitory memory having recorded thereon a computer program comprising instructions that when executed by the processor causes the processor to perform machine-learning by being configured to:
obtain 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

teach the neural network; and/or

causes the processor to perform 3D design by being configured to:
obtain a neural network taught according to machine-learning by being configured to:
obtain the architecture for the neural network which is configured to take as the input the 2D sketch, and to output the 3D model represented by the 2D sketch, the 3D model being a parameterized 3D model defined by the set of parameters consisting of the first subset of one or more parameters and the second subset of one or more parameters, and the neural network is configured to selectively:
output the value for the set, and
take as input the value for the first subset from the user, and

output the value for the second subset; and
teach the neural network;

obtain a 2D sketch;
obtain, from the user, a value for the first subset; and

apply the neural network to the 2D sketch and taking as input the value for the first subset from the user, to output a value for the second subset,
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
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.