CPC G06N 3/08 (2013.01) [G06F 18/214 (2023.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G06V 20/64 (2022.01)] | 16 Claims |
1. A method for training a model, the method comprising:
generating a plurality of synthetic images, the generation including selecting parameters of environmental features, camera intrinsics, and a target object, the target object being a simulation of a physical object, wherein the generation of the plurality of synthetic images includes generating a greater number of synthetic images assigned high probabilistic weights than low probabilistic weights, the assigned probabilistic weights representing a likelihood of the target object being associated with the selected parameters;
annotating the plurality of synthetic images with information related to properties of the target object; and
training the model to detect the physical object using the plurality of annotated synthetic images.
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