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

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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Bibliographic Details
Main Authors: Qichen Su, Haza Nuzly Abdull Hamed, Mohd Adham Isa, Xue Hao, Xin Dai
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Data augmentation
data imbalance
generative adversarial networks
skin lesion classification
Online Access:https://ieeexplore.ieee.org/document/10416885/

Internet

https://ieeexplore.ieee.org/document/10416885/

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