Sep 1, 2021 · Data augmentation is one of the most important recipes for the stability of neural network training. Compared to traditional approaches such as ...

Sep 21, 2021 · However in practical medical image analysis, available training data are often limited, often causing over-fitting during model training. In ...

Oct 2, 2021 · However in practical medical image analysis, available training data are often limited, often causing over-fitting during model training. In ...

Sep 27, 2021 · In this paper, a novel data augmentation method is proposed to effectively alleviate the over-fitting issue, not in the input space but in the logit space.

This study thoroughly explores diverse applications of Deep learning-based data augmentation in medical imaging, commonly used datasets, evaluation metrics, ...

In this paper, we propose a novel data augmentation method for medical image segmentation without losing the semantics of the key objects (e.g., polyps). This ...

Types of image augmentations include rotation, cropping, zooming, color range changes, grayscaling, and flipping.

Feb 27, 2023 · Commonly used augmentation techniques with eye fundus images to boost the performance of deep learning based approaches are rotation, shearing, flipping, and ...

Aug 27, 2024 · Recent multimodal text-image supervised foundation models offer new solutions to data scarcity through effective representation learning.

Mar 8, 2023 · This study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The research aims to enhance the classifier's generalization ...