Domain > evanrosica.com

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DNS Resolutions

Date	IP Address
2021-01-11	52.217.104.123 (ClassC)
2021-02-05	52.217.75.59 (ClassC)
2021-02-17	52.217.91.27 (ClassC)
2021-03-07	52.217.94.43 (ClassC)
2022-11-30	52.216.215.45 (ClassC)
2022-12-05	52.216.59.237 (ClassC)
2023-04-29	54.231.228.77 (ClassC)
2023-04-30	52.217.120.69 (ClassC)
2023-05-20	52.217.123.141 (ClassC)
2024-09-17	52.217.139.133 (ClassC)
2024-09-30	52.216.54.157 (ClassC)
2024-10-14	52.217.67.51 (ClassC)
2025-01-01	52.217.230.141 (ClassC)
2025-01-23	52.216.138.122 (ClassC)
2025-04-12	3.5.1.142 (ClassC)
2025-05-12	52.216.218.34 (ClassC)
2025-07-28	3.5.20.7 (ClassC)
2025-08-10	52.216.140.19 (ClassC)
2025-09-23	52.217.80.219 (ClassC)
2026-01-16	52.217.101.203 (ClassC)

HTTP/1.1 200 OKx-amz-id-2: SGSo4aWG7NaUYKt5n5eRNrNJo9fMKqVHlhRX82z2sLFC7VsKnTuiiWzI4UhJ/QGUj7wST39+lbIx-amz-request-id: 1FEK9Y7XC9CN9Y1KDate: Tue, 17 Sep 2024 13:46:44 GMTLast-Modified: Sat, 30 Mar 20

html xmlnshttp://www.w3.org/1999/xhtml >head>    title>GANArt Project Homepage/title>/head>body>	h1> Generative Art Via Neural Networks /h1>	We examine to what extent neural networks can be used to create art. Our criteria is that the generated images must be novel, detailed, and aesthetically pleasing.	We evaluate two state-of-the-art approaches against our criteria: neural style transfer (NST) as in a hrefhttp://evanrosica.com/GANArt/cezanne/>Johnson et al./a>br />	and unpaired image-to-image translation (IIT) as in a hrefhttps://arxiv.org/pdf/1703.10593.pdf>Zhu et al./a>br />    	p>We show that both methods meet our criteria in different ways. NST works best when trained on abstract images as well those with geometric patterns, while IIT works better on less abstract images. 	p>We discuss several undiscovered problems with these methods. 	We mathematically prove that the implementation of the “cycle consistency constraint” in Zhu et al. is unnecessarily complex. We also observe that their method has the undesirable property of converging to the test image as the test image becomes relatively large. 	p>We believe that our comparison between IIT and NST is the most extensive yet done, and the only one to consider very large images.	h3> Read the Paper:a hrefhttp://evanrosica.com/GANArt/Final Paper_Compressed.pdf>Here/a>/h3>	h3> My :a hrefhttps://github.com/errosica>github/a>/h3>			h3> CycleGAN output - Browse by Artist: /h3>    p>a hrefhttp://evanrosica.com/GANArt/cezanne/>Cezanne/a>br />	p>a hrefhttp://evanrosica.com/GANArt/monet/>Monet/a>br />	p>a hrefhttp://evanrosica.com/GANArt/ukiyoe/>Ukiyo-e/a>br />	p>a hrefhttp://evanrosica.com/GANArt/vangogh/>Van Gogh/a>br />	    h3> Neural Style Transfer output /h3>    p>a hrefhttp://evanrosica.com/GANArt/Neural_Style_Transfer/>Neural_Style_Transfer/a>br />	p>a hrefhttp://evanrosica.com>Home/a>br />/body>/html>

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Domain > evanrosica.com

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