PSNR: 33.24SSIM: 0.9071
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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: 33.30SSIM: 0.9083
PSNR: 33.14SSIM: 0.9058
PSNR: 35.36SSIM: 0.9302
PSNR: 33.22SSIM: 0.9103
PSNR: 33.38SSIM: 0.9089
PSNR: 32.36SSIM: 0.8984
PSNR: 35.17
PSNR: 34.34SSIM: 0.9240
PSNR: 34.43SSIM: 0.9247
PSNR: 32.46SSIM: 0.8968
PSNR: 25.63SSIM: 0.74
PSNR: 30.49SSIM: 0.8628
PSNR: 20.39SSIM: 0.515
PSNR: 34.12SSIM: 0.9223
PSNR: 34.25
PSNR: 29.4SSIM: 0.8472MOS: 3.58
PSNR: 34.24SSIM: 0.9224