At Computer-Vision-meets-Astronomy group meeting this morning, several extremely good ideas were hatched. One idea, from Lang originally in part, is to build a model of heterogeneous JPEG images of the sky grabbed from the Web but using not true brightness on a linear or magnitude scale but just brightness ranking. This would get us much of the information we seek about the sky without putting nearly as hard requirements on our PSF and photometric calibration.
Another idea, hatched by Schölkopf after an amazing image-recognition demonstration by Fergus, was to start a company (non-profit) that provides a browser plug-in or skin that delivers image-labeling content to a public database, rather than letting it just get sucked into the black hole that is Google Corporation. The idea is that whenever you do a Google image search, Google learns image labels by looking at which images you subsequently click, or so we hypothesize; that's valuable content, since all high-performing image recognition systems (except Astrometry.net) are data-driven. (A related idea was to start a class-action lawsuit to get everyone's image-labeling data back from Google!)
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