CPC G06V 20/35 (2022.01) [G06F 16/24578 (2019.01); G06F 16/285 (2019.01); G06F 16/51 (2019.01); G06F 16/583 (2019.01); G06F 18/217 (2023.01); G06F 18/2113 (2023.01); G06F 18/23213 (2023.01); G06F 18/24147 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06N 20/10 (2019.01)] | 19 Claims |
1. A computer-implemented method comprising:
inputting an image into a trained image classifier, wherein the trained image classifier is based on a recursive clustering process that generates data clusters, wherein a step in the recursive clustering process comprises partitioning data into clusters and recombining all clusters from the clusters with a size exceeding a predefined threshold prior to a subsequent partitioning;
determining, for the image, a related data cluster from the data clusters of the trained image classifier, the related data cluster comprising a set of training images and corresponding tags; and
propagating a tag to the image, the tag selected from the corresponding tags of the set of training images.
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