2023
DOI: 10.3390/electronics12030654
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Stacked Siamese Generative Adversarial Nets: A Novel Way to Enlarge Image Dataset

Abstract: Deep neural networks often need to be trained with a large number of samples in a dataset. When the training samples in a dataset are not enough, the performance of the model will degrade. The Generative Adversarial Network (GAN) is considered to be effective at generating samples, and thus, at expanding the datasets. Consequently, in this paper, we proposed a novel method, called the Stacked Siamese Generative Adversarial Network (SSGAN), for generating large-scale images with high quality. The SSGAN is made … Show more

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