Patent ID: 11869139
Assignee: PACKSIZE LLC
Field: Audio-visual technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 0:
1. A computer system for training a convolutional neural network to classify patches of an object as clean or defective based upon a feature vector, the computer system comprising:
one or more processors; and
one or more computer-readable media having stored thereon executable instructions that when executed by the one or more processors configure the computer system to:
receive a plurality of training 3D models of objects and corresponding training classifications,
render a plurality of views of the 3D models with controlled lighting to generate training data,
compute a plurality of feature vectors from the views by the convolutional neural network, wherein the plurality of feature vectors are based upon a plurality of features rendered within the plurality of views,
compute parameters of the convolutional neural network,
compute a training error metric between the training classifications of the training 3D models with outputs of the convolutional neural network configured based on the parameters,
compute a validation error metric in accordance with a plurality of validation 3D models separate from the training 3D models, and
in response to determining that the training error metric and the validation error metric satisfy a threshold, configure the neural network in accordance with the parameters.