PSNR: 29.47SSIM: 0.8015
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Image Super-Resolution
Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.
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PSNR: 29.36SSIM: 0.7996
PSNR: 29.54SSIM: 0.8025
PSNR: 33.05SSIM: .9126
PSNR: 33.52
PSNR: 33.77SSIM: 0.922
PSNR: 29.44
PSNR: 33.03
PSNR: 33.03
PSNR: 29.30SSIM: 0.7985
PSNR: 34.09SSIM: 0.921
PSNR: 33.04
PSNR: 33.55
PSNR: 33.82
PSNR: 33.78SSIM: 0.921
PSNR: 29.49SSIM: 0.8041
PSNR: 29.51SSIM: 0.8019
PSNR: 32.94SSIM: 0.9144
PSNR: 30.79
PSNR: 33.63
PSNR: 33.7
PSNR: 33.97SSIM: 0.922
PSNR: 33.62SSIM: 0.9178