Integrated bottom-up segmentation for semi-supervised image segmentation

Abstract

Embodiments of the present disclosure include a computer-implemented method, a system, and a computer program product for integrating bottom-up segmentation techniques into a semi-supervised image segmentation machine learning model. The computer implemented method includes training a machine learning model with a labeled dataset. The labeled dataset includes ground truth segmentation labels for each sample in the labeled dataset. The computer implemented method also includes generating a pseudo labeled dataset by applying an unlabeled dataset to the machine learning model using a top-down segmentation grouping rule. The computer implemented method further includes evaluating the pseudo labeled dataset using a bottom-up segmentation grouping rule to produce evaluation results, combining the pseudo labeled dataset with the second pseudo labeled dataset into a training dataset, and then retraining the machine learning model with the training dataset.