This paper proposes a novel strategy that employs Generative Adversarial Networks (GANs) to augment data in the image segmentation field, ...

Abstract—This paper proposes a novel strategy that em- ploys Generative Adversarial Networks (GANs) to augment data in the image segmentation field, ...

Aug 18, 2023 · We propose a novel adversarial learning-based framework called Efficient-GAN (EGAN) that uses an unsupervised generative network to generate accurate lesion ...

It is a non-invasive skin imaging technique that acquires enlarged and reduced images of skin lesion regions to increase the sharpness of the spots, which ...

This Master thesis uses generative adversarial networks to generate synthetic data to augment the classification model's training datasets to boost ...

For the first problem, we introduce a Generative Adversarial Networks (GANs)-based method for generating realistic synthetic data to improve generalization of.

In this study, a generative adversarial network is proposed, with global and local semantic feature awareness (GLSFA-GAN) for skin lesion segmentation based on ...

In this work, we present a novel approach for skin lesion segmentation through leveraging generative adversarial networks.

Feb 26, 2020 · We introduce a data augmentation method using deep convolutional generative adversarial network (DCGAN), which can generate realistic samples with lesion ...

Oct 22, 2024 · In this study, a generative adversarial network is proposed, with global and local semantic feature awareness (GLSFA-GAN) for skin lesion ...