Abstract: Generative Adversarial Networks (GANs) have demonstrated remarkable capability in synthesizing high-quality images from limited data, addressing challenges of data scarcity and diversity in ...
Abstract: Deep learning methods rely on large labeled datasets. However, in real-world applications such as medical imaging, only scarcely labeled datasets might be available. Semi-supervised deep ...
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