Amazon technologies, inc. (20250148644). DYNAMIC GENERATION OF DATA SETS FOR TRAINING MACHINE-TRAINED NETWORK
DYNAMIC GENERATION OF DATA SETS FOR TRAINING MACHINE-TRAINED NETWORK
Organization Name
Inventor(s)
Andrew C. Mihal of San Jose CA US
Steven L. Teig of Menlo Park CA US
DYNAMIC GENERATION OF DATA SETS FOR TRAINING MACHINE-TRAINED NETWORK
This abstract first appeared for US patent application 20250148644 titled 'DYNAMIC GENERATION OF DATA SETS FOR TRAINING MACHINE-TRAINED NETWORK
Original Abstract Submitted
some embodiments of the invention provide a novel method for training a multi-layer node network. some embodiments train the multi-layer network using a set of inputs generated with random misalignments incorporated into the training data set. in some embodiments, the training data set is a synthetically generated training set based on a three-dimensional ground truth model as it would be sensed by a sensor array from different positions and with different deviations from ideal alignment and placement. some embodiments dynamically generate training data sets when a determination is made that more training is required. training data sets, in some embodiments, are generated based on training data sets for which the multi-layer node network has produced bad results.
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