Training neural networks to detect similar three-dimensional objects using fuzzy identification
AssigneeMicrosoft Technology Licensing, LLC
InventorsFredrik Carl Anders LJUNG LARHED, Hans-Ulrik Tord LINDAHL
Life of this patent
Estimating the term…
Abstract
A system for training a neural network generates a plurality of training meshes based on an input mesh. The plurality of training meshes include at least one mesh perceptually similar to the input mesh and one arbitrarily selected mesh perceptually dissimilar to the input mesh. The neural network is trained using the input mesh and the plurality of training meshes by tuning output of the neural network to identify similar non-identical meshes. The trained neural network is robust in identifying meshes similar to an unknown mesh input to the trained neural network.
Claims20
A system for training a neural network, the system comprising:
- at least one processor;
- and
- at least one memory comprising computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the at least one processor to:
- generate a plurality of training meshes based on an input mesh, at least one of the training meshes being a mesh having similar properties to the input mesh, wherein at least one property of the mesh being different than a property of the input mesh, at least another one of the training meshes being a mesh having dissimilar properties to the input mesh, wherein at least a plurality of the properties of the mesh being different than a plurality of properties of the input mesh;
- extract properties from the input mesh and the plurality of training meshes;
- compute values for the extracted properties, the computed values being inputs to a neural network to be trained;
- input the computed values to the neural network to generate corresponding output values;
- adjust the neural network to (i) converge the output values for the input mesh and the mesh having similar properties to the input mesh and (ii) diverge the output values for the input mesh and the mesh having dissimilar properties to the input mesh, to train the neural network;
- and
- use the trained neural network to identify meshes similar to an unknown mesh input to the trained neural network.
A computerized method for training a neural network, the computerized method comprising:
- generating a plurality of training meshes based on an input mesh, the plurality of training meshes including at least one mesh perceptually similar to the input mesh and one arbitrarily selected mesh perceptually dissimilar to the input mesh;
- training the neural network using the input mesh and the plurality of training meshes by tuning output of the neural network to identify similar non-identical meshes;
- and
- using the trained neural network to identify meshes similar to an unknown mesh input to the trained neural network.
One or more computer storage media having computer-executable instructions for training a neural network that, upon execution by a processor, cause the processor to at least:
- generate a plurality of training meshes based on an input mesh, the plurality of training meshes including at least one mesh perceptually similar to the input mesh and one arbitrarily selected mesh perceptually dissimilar to the input mesh;
- train the neural network using the input mesh and the plurality of training meshes by tuning the output of the neural network to identify similar meshes;
- and
- use the trained neural network to identify meshes similar to an unknown mesh input to the trained neural network.
Dependencies are inferred from the claim text.