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- W2904101609 abstract "Single Image Super-Resolution techniques have the function of retrieving a high resolution image from a single low resolution input. They implement deep learning heuristics which perform the techniques to form pixel-accourate reproductions. In this paper we have experimented upon various neural architectures with unique approaches towards the task of super-resolution. We have especially elaborated upon adversarial training networks which are yielding progressive results in both conditional and quantifiable benchmarks." @default.
- W2904101609 created "2018-12-22" @default.
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- W2904101609 date "2018-12-14" @default.
- W2904101609 modified "2023-09-25" @default.
- W2904101609 title "Understanding Single Image Super-Resolution Techniques with Generative Adversarial Networks" @default.
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- W2904101609 doi "https://doi.org/10.1007/978-981-13-1592-3_66" @default.
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