Implementation of Generative Adversarial Networks in Mobile Applications for Image Data Enhancement
DOI:
https://doi.org/10.13052/jmm1550-4646.1938Keywords:
artificial intelligence, machine learning, ML, deep learning, DL, neural networks, generative adversarial network, GAN, super resolution, SR, low resolution, LR, SRGANAbstract
This article aims to explore and research GANs as a tool for mobile devices that can generate high-resolution images from low-resolution samples and reduce blurring. In addition, the authors also analyse the specifics of GAN, SRGAN, and ESRGAN loss functions and their features. GANs are widely used for a vast range of applied tasks for image manipulations. They’re able to synthesize, combine, and restore graphical samples of high quality that are almost indistinguishable from real data. The main scope of the research is to study the possibility to use GANs for the said tasks, and their potential implementation in mobile applications.
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