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Enhancing resolution in coherent microscopy using deep learning

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Abstract

A generative adversarial network (GAN) based super-resolution framework is presented. This deep learning-based framework is capable of enhancing the resolution of coherent imaging systems in both pixel size-limited and diffraction-limited microscopy systems.

© 2019 The Author(s)

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