CPC G06N 3/084 (2013.01) [G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01); G06V 40/165 (2022.01); G06V 40/169 (2022.01); G06V 40/174 (2022.01); G06V 40/179 (2022.01)] | 25 Claims |
1. A computer-implemented method for machine learning comprising:
obtaining facial images for a neural network training dataset;
encoding facial elements from the facial images into one or more vector representations of the facial elements using a machine learning neural network;
training a generative adversarial network (GAN) generator to provide one or more synthetic vectors based on the one or more vector representations, wherein a feature selector selects values from the one or more vector representations, the values being used as an input to the GAN, and wherein the one or more synthetic vectors enable avoidance of discriminator detection in the GAN;
generating additional synthetic vectors in the GAN, wherein the additional synthetic vectors avoid discriminator detection; and
further training the machine learning neural network, using the additional synthetic vectors that were generated by the GAN based on the selected values of the feature selector.
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