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Learning to process images depicting faces without leveraging sensitive attributes in deep learning models
Learning to process images depicting faces without leveraging sensitive attributes in deep learning models
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机译：学会在不利用深度学习模型中的敏感属性的情况下处理描述面孔的图像
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摘要
Systems, methods, and articles of manufacture to generate, by a neural network of a variational autoencoder, a latent vector for a first input image, generate, by the neural network of the variational autoencoder, a first reconstructed image by sampling the latent vector for the first input image, determine a reconstruction loss incurred in generating the first reconstructed image based at least in part on: (i) a difference of the first input image and the first reconstructed image, and (ii) a master model trained to detect a sensitive attribute in images, determine a total loss based at least in part on the reconstruction loss and a classification loss, and optimize a plurality of weights of the neural network of the variational autoencoder based on a backpropagation operation and the determined total loss, the optimized neural network trained to not consider the sensitive attribute in images.
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