Abstract: Described herein are systems, software, and methods for generating training datasets for machine learning (ML) applications. The systems, software, and methods generally operate by obtaining first and second pluralities of images of a subject bearing as associated imaging label, identifying locations of the imaging label within the first plurality of images, and using the identified locations to generate a plurality of labeled images based upon the second plurality of images. In this manner, a large collection of labeled images may be collected without the need for manual labeling by a human actor. This large collection of labeled images may then form the training set for training a ML system.

Abstract: Described herein are systems, software, and methods for generating training datasets for machine learning (ML) applications. The systems, software, and methods generally operate by obtaining first and second pluralities of images of a subject bearing as associated imaging label, identifying locations of the imaging label within the first plurality of images, and using the identified locations to generate a plurality of labeled images based upon the second plurality of images. In this manner, a large collection of labeled images may be collected without the need for manual labeling by a human actor. This large collection of labeled images may then form the training set for training a ML system.