Active Learning

Active learning as a framework has a straight objective to select the data points that would be most beneficial for the deep learning model to learn from. As a cyclic framework it consists of Training pool, a machine learning, a strategy to estimate uncertainty of unlabeled data points, unlabeled pool of data and an Oracle that annotates the data. The cyclic framework is in short a data engine that is designed to keep improving the machine learning model.

In MONAI label, we allow for a random sampling strategy as a way to select the data.