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View all- Wei TCao DZheng CYang Q(2020)A simulation-based few samples learning method for surface defect segmentationNeurocomputing10.1016/j.neucom.2020.06.090412(461-476)Online publication date: Oct-2020
Generative adversarial network (GAN) is a powerful generative model. However, it suffers from several problems, such as convergence instability and mode collapse. To overcome these drawbacks, this paper presents a novel architecture of GAN, which ...
Generative Adversarial Networks (GANs) is a novel class of deep generative models that has recently gained significant attention. GANs learn complex and high-dimensional distributions implicitly over images, audio, and data. However, there exist major ...
Generative adversarial network (GAN) is a powerful generative model. However, it suffers from gradient vanishing, divergence mismatching and mode collapse. To overcome these problems, we propose a novel GAN, which consists of one generator G and two ...
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