Active Learning for Cell Imaging

One of the main obstacles standing in front of many machine learning tasks is the lack of labeled data. Labeling data might be exhausting and expensive. Thus, many times it is not reasonable to even try to solve a problem using machine learning methods due to lack of labels. To alleviate this problem, a field in machine learning has emerged, called Active Learning. Active Learning is a method in machine learning that provides a framework for prioritizing the unlabeled data samples based on the labeled data that a model already saw.