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- W3010247039 abstract "The process of obtaining high resolution image from the low resolution image available is called Single Image Super Resolution (SISR). But the issue is that many regions in the obtained high resolution image are not as clearly visible as in the actual low resolution image. So our aim is to achieve high resolution image from available low resolution image with all details intact. There are few models which have been successful in achieving this; however, there is a trade-off between obtaining results with high values of standard measurement parameters (psnr, ssim etc) and results which appear clear and realistic. So we propose a model based on Deep Convolutional Neural Networks which is capable of achieving results which have good values of standard measurement parameters and are visually clear and realistic." @default.
- W3010247039 created "2020-03-13" @default.
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- W3010247039 date "2018-05-01" @default.
- W3010247039 modified "2023-09-26" @default.
- W3010247039 title "Single Image Super ResolutionUSingDeep Convolutional Neural Networks" @default.
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- W3010247039 doi "https://doi.org/10.1109/rteict42901.2018.9012445" @default.
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