Derin öğrenme destekli süper örnekleme (Turkish Wikipedia)

Analysis of information sources in references of the Wikipedia article "Derin öğrenme destekli süper örnekleme" in Turkish language version.

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digitaltrends.com

  • "Nvidia RTX DLSS: Everything you need to know". Digital Trends. 14 Şubat 2020. 2 Kasım 2018 tarihinde kaynağından arşivlendi. Erişim tarihi: 5 Nisan 2020. Deep learning super sampling uses artificial intelligence and machine learning to produce an image that looks like a higher-resolution image, without the rendering overhead. Nvidia’s algorithm learns from tens of thousands of rendered sequences of images that were created using a supercomputer. That trains the algorithm to be able to produce similarly beautiful images, but without requiring the graphics card to work as hard to do it. 

eurogamer.net

nvidia.com

  • "NVIDIA DLSS: Control and Beyond". nividia.com. 30 Ağustos 2019. 10 Nisan 2020 tarihinde kaynağından arşivlendi. Erişim tarihi: 11 Ağustos 2020. we developed a new image processing algorithm that approximated our AI research model and fit within our performance budget. This image processing approach to DLSS is integrated into Control 

techspot.com

  • "Battlefield V DLSS Tested: Overpromised, Underdelivered". techspot.com. 19 Şubat 2019. 19 Şubat 2019 tarihinde kaynağından arşivlendi. Erişim tarihi: 6 Nisan 2020. Of course, this is to be expected. DLSS was never going to provide the same image quality as native 4K, while providing a 37% performance uplift. That would be black magic. But the quality difference comparing the two is almost laughable, in how far away DLSS is from the native presentation in these stressful areas. 
  • "Nvidia DLSS in 2020: stunning results". techspot.com. 26 Şubat 2020. 28 Şubat 2020 tarihinde kaynağından arşivlendi. Erişim tarihi: 5 Nisan 2020. 

web.archive.org

  • "Nvidia RTX DLSS: Everything you need to know". Digital Trends. 14 Şubat 2020. 2 Kasım 2018 tarihinde kaynağından arşivlendi. Erişim tarihi: 5 Nisan 2020. Deep learning super sampling uses artificial intelligence and machine learning to produce an image that looks like a higher-resolution image, without the rendering overhead. Nvidia’s algorithm learns from tens of thousands of rendered sequences of images that were created using a supercomputer. That trains the algorithm to be able to produce similarly beautiful images, but without requiring the graphics card to work as hard to do it. 
  • "Battlefield V DLSS Tested: Overpromised, Underdelivered". techspot.com. 19 Şubat 2019. 19 Şubat 2019 tarihinde kaynağından arşivlendi. Erişim tarihi: 6 Nisan 2020. Of course, this is to be expected. DLSS was never going to provide the same image quality as native 4K, while providing a 37% performance uplift. That would be black magic. But the quality difference comparing the two is almost laughable, in how far away DLSS is from the native presentation in these stressful areas. 
  • "Remedy's Control vs DLSS 2.0 – AI upscaling reaches the next level". Eurogamer. 4 Nisan 2020. 4 Nisan 2020 tarihinde kaynağından arşivlendi. Erişim tarihi: 5 Nisan 2020. Of course, this isn't the first DLSS implementation we've seen in Control. The game shipped with a decent enough rendition of the technology that didn't actually use the machine learning 
  • "Nvidia DLSS in 2020: stunning results". techspot.com. 26 Şubat 2020. 28 Şubat 2020 tarihinde kaynağından arşivlendi. Erişim tarihi: 5 Nisan 2020. 
  • "NVIDIA DLSS: Control and Beyond". nividia.com. 30 Ağustos 2019. 10 Nisan 2020 tarihinde kaynağından arşivlendi. Erişim tarihi: 11 Ağustos 2020. we developed a new image processing algorithm that approximated our AI research model and fit within our performance budget. This image processing approach to DLSS is integrated into Control