A Stacked Generalization U-shape network based on zoom strategy and its application in biomedical image segmentation.
Journal:
Computer methods and programs in biomedicine
Published Date:
Jul 30, 2020
Abstract
BACKGROUND AND OBJECTIVE: The deep neural network model can learn complex non-linear relationships in the data and has superior flexibility and adaptability. A downside of this flexibility is that they are sensitive to initial conditions, both in terms of the initial random weights and in terms of the statistical noise in the training dataset. And the disadvantage caused by adaptability is that deep convolutional networks usually have poor robustness or generalization when the models are trained using the extremely limited amount of labeled data, especially in the biomedical imaging informatics field.