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Smart gan is a novel approach that addresses the problem of selecting the most appropriate gan model for generating synthetic images in the intermediate stage of a deep learning pipeline It uses a reinforcement learning approach, a subset of machine learning techniques that learns through interaction and feedback with the environment. By doing so, we succeed on alleviating the gradient vanishing issue Hence, our work offers a new perspective on improving gan performance.
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