Comment Re:So the Pre 1.0 makes me appreciate my Treo 755p (Score 2, Informative) 283
Classic will allow you to run Agendus on the Pre. If you can adjust to the hardware differences, it might be worth considering.
Comment Re:Let's Stand Up - A Call to Action (mildly O/T) (Score 4, Informative) 241
Why don't we, through
Submission + - Algorithm That Seemlesly Patches Holes in Images (cmu.edu)
Beetle B. writes: "From the site:
'What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data-driven, requiring no annotations or labelling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of image completions and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches.'
English translation: The algorithm replaces arbitrarily shaped blank areas in an image with portions of images from a huge catalog in a totally seamless manner."
'What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data-driven, requiring no annotations or labelling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of image completions and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches.'
English translation: The algorithm replaces arbitrarily shaped blank areas in an image with portions of images from a huge catalog in a totally seamless manner."
