Biomedical image classification made easier thanks to transfer and semi-supervised learning.
Journal:
Computer methods and programs in biomedicine
Published Date:
Oct 3, 2020
Abstract
BACKGROUND AND OBJECTIVES: Deep learning techniques are the state-of-the-art approach to solve image classification problems in biomedicine; however, they require the acquisition and annotation of a considerable volume of images. In addition, using deep learning libraries and tuning the hyperparameters of the networks trained with them might be challenging for several users. These drawbacks prevent the adoption of these techniques outside the machine-learning community. In this work, we present an Automated Machine Learning (AutoML) method to deal with these problems.