A GAN-Based Data Augmentation Method for Imbalanced Multi-Class Skin Lesion Classification

Skin cancer is one of the most common types of cancer globally. Despite the remarkable advancements of deep learning methods in computer vision, automatic diagnosis of skin diseases still faces challenges such as limited data and class imbalance. Generative Adversarial Networks (GANs), which can syn...

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Главные авторы:	Qichen Su, Haza Nuzly Abdull Hamed, Mohd Adham Isa, Xue Hao, Xin Dai
Формат:	Artigo
Язык:	Inglês
Опубликовано:	IEEE 2024-01-01
Серии:	IEEE Access
Предметы:	Data augmentation data imbalance generative adversarial networks skin lesion classification
Online-ссылка:	https://ieeexplore.ieee.org/document/10416885/
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