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  2. waifu2x - Wikipedia

    en.wikipedia.org/wiki/Waifu2x

    waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1] waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN). [2] [3] It uses Nvidia CUDA for computing, [4] although alternative implementations that allow for OpenCL [5] and Vulkan [6] have been created.

  3. hqx (algorithm) - Wikipedia

    en.wikipedia.org/wiki/Hqx_(algorithm)

    hqx ("high quality scale") is a set of 3 image upscaling algorithms developed by Maxim Stepin. The algorithms are hq2x , hq3x , and hq4x , which magnify by a factor of 2, 3, and 4 respectively. It was initially created in 2003 for the Super NES emulator ZSNES , [ 1 ] and is used in emulators such as Nestopia , F. CEUX Snes9x., and Snes9x .

  4. Deep learning super sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    Nvidia advertised DLSS as a key feature of the GeForce 20 series cards when they launched in September 2018. [5] At that time, the results were limited to a few video games, namely Battlefield V, [6] or Metro Exodus, because the algorithm had to be trained specifically on each game on which it was applied and the results were usually not as good as simple resolution upscaling.

  5. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.

  6. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations with no loss of image quality. When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated. In the case of decreasing the pixel number (scaling down), this usually ...

  7. Deep learning anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_anti-aliasing

    Deep learning anti-aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. [1] DLAA depends on and requires Tensor Cores available in Nvidia RTX cards. [1]DLAA is similar to deep learning super sampling (DLSS) in its anti-aliasing method, [2] with one important differentiation being that the goal of DLSS is to increase performance at the cost of image quality, [3] whereas the ...

  8. Scale AI valued at $14 billion in Nvidia, Amazon-backed ... - AOL

    www.aol.com/news/scale-ai-valued-14-billion...

    (Reuters) -Scale AI said on Tuesday it had raised $1 billion in a late-stage funding round led by venture capital firm Accel with participation from tech giants Nvidia, Amazon, and Meta, valuing ...

  9. Fast approximate anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Fast_approximate_anti-aliasing

    The input data is the rendered image and optionally the luminance data. [3]Acquire the luminance data. [3] This data could be passed into the FXAA algorithm from the rendering step as an alpha channel embedded into the image to be antialiased, calculated from the rendered image, or approximated by using the green channel as the luminance data.