Adaptive normalized data augmentation algorithm based on DCGAN
To address this issue,this paper proposes an adaptive normalized data augmentation algorithm based on DCGAN.Firstly,the powerful feature extraction capability of the DCGAN improves the realism of the generated images.Subsequently,using adaptive instance normalization to solve the problem of network overfitting caused by gradient explosion.On this basic,the model was trained on the CIFAR10 dataset,and the input original sample image was subjected to 1 000 rounds of confrontation to obtain the generated image.Finally,experimental results show that the adaptive normalization method proposed in this article improves the authenticity of the generated images by 1.2％.
NETL
NSTL
万方数据
维普
