PSNR: 35.09SSIM: 0.9505
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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: 34.89SSIM: 0.9487
PSNR: 35.16SSIM: 0.9505
PSNR: 33.04SSIM: 0.937
PSNR: 34.94
PSNR: 30.76
PSNR: 30.74
PSNR: 32.92SSIM: 0.935
PSNR: 30.75
PSNR: 33.54SSIM: 0.9402
PSNR: 34.54SSIM: 0.9474
PSNR: 31.93
PSNR: 32.878
PSNR: 32.62
PSNR: 33.12SSIM: 0.938
PSNR: 36.10SSIM: 0.9580
PSNR: 33.25SSIM: 0.9386
PSNR: 32.17
PSNR: 33.5
SSIM: 0.9875
PSNR: 32.3
PSNR: 32.83SSIM: 0.9353
PSNR: 32.78SSIM: 0.9342
PSNR: 33.53SSIM: 0.9398
PSNR: 32.07SSIM: 0.9277