PSNR: 38.19SSIM: 0.9617
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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.
논문
PSNR: 37.53
PSNR: 41.01SSIM: 0.9831
PSNR: 37.58
PSNR: 37.45SSIM: 0.9570
PSNR: 38.08SSIM: 0.96
PSNR: 37.63
PSNR: 41.14SSIM: 0.9842
PSNR: 37.13SSIM: .9569
PSNR: 37.82
PSNR: 37.76
PSNR: 38.242
PSNR: 38.11
PSNR: 38.13SSIM: 0.961
PSNR: 41.22SSIM: 0.9846
PSNR: 41.13SSIM: 0.9836
PSNR: 36.69SSIM: 0.94
PSNR: 37.66SSIM: 0.9599
PSNR: 37.42
PSNR: 35.05
PSNR: 37.66SSIM: 0.9585
PSNR: 38.00
PSNR: 37.91
PSNR: 37.57
PSNR: 38.21SSIM: 0.9614
PSNR: 38.22SSIM: 0.9612
PSNR: 38.05SSIM: 0.9606
PSNR: 40.77
PSNR: 29.24