Pytorch implementation of Generative Adversarial Networks (GAN) for MNIST and EMNIST datasets
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Updated
Jul 3, 2018 - Python
Pytorch implementation of Generative Adversarial Networks (GAN) for MNIST and EMNIST datasets
Comparison of two QR code super-resolution models (GAN vs. CNN) focused on pixel accuracy, scannability, and practical use in logistics, healthcare, and digital applications.
Chess game including state-of-the-art GUI, lichess.org game selection interface and review mechanic and a simple computer opponent to play against.
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