CPC G06N 20/00 (2019.01) [G06F 18/217 (2023.01); G06F 18/231 (2023.01); G06N 3/08 (2013.01); G06N 20/20 (2019.01); G06T 7/0002 (2013.01); G06V 10/255 (2022.01); G06V 10/7625 (2022.01); G06V 10/776 (2022.01); G06V 20/42 (2022.01); G06V 40/103 (2022.01); G06N 3/045 (2023.01)] | 20 Claims |
1. A method comprising:
receiving, by a parent inference model of a network device, data indicating a sub-classification of a sample object and a sample image that includes the sample object, wherein the network device further includes a child inference model, and the parent inference model and the child inference model each performs object recognition;
generating, by the parent inference model, a bounding box that indicates a region of interest with respect to the sample object;
identifying, by the parent inference model, a first general classification of the sample object included in the sample image;
generating, by the parent inference model, sample data indicating the first general classification of the sample object;
replacing the sample data with the data indicating the sub-classification; and
training the child inference model using the sample image, the bounding box, and the data indicating the sub-classification.
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