Image generation method based on adaptive gradient cutting under differential privacy protection
A differential privacy, image generation technology, applied in 2D image generation, image enhancement, image analysis and other directions, can solve problems such as unreasonable cropping and adding noise, and achieve the effect of fast training convergence and high image quality.
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[0061] Generate huge amounts of data subject to network trained to generate photorealistic image data, and the training process gradient or after training network weights are leaked reasoning model could allow an attacker to attack members of reasoning or an attack by guessing whether the training data data. Therefore, to ensure the privacy of the training process to generate a model, generating a network comprising a two-part structure, respectively, is determined and generator. Both the neural network, thus training process is similar to the training data is approximately the input network obtained results, the calculated loss function based on the results obtained derivative of the loss function or the gradient discriminator generator. According to the nature of the post-processing differential privacy, just training process satisfies the differential discriminator privacy protection, generator training process naturally also meet the definition of differential privacy. So befo...
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