CPC G06F 18/241 (2023.01) [G06F 18/211 (2023.01); G06N 3/084 (2013.01)] | 20 Claims |
1. A computer-implemented method comprising:
inputting corresponding pairs of a plurality of training images to an image classifier, wherein respective pairs of the corresponding pairs comprise at least two images having a same classification and different augmentations; and
training an artificial neural network of the image classifier to classify the plurality of training images using an augmentation loss function, wherein the augmentation loss function reduces differences in model outputs between the corresponding pairs of the plurality of training images, and wherein a difference in the model outputs for a first pair of the corresponding pairs is associated with a coefficient, wherein the coefficient is relatively larger when the different augmentations comprise a single augmentation, and wherein the coefficient is relatively smaller when the different augmentations comprise a combination of multiple augmentations.
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