When you search for images on the Web, you use a search engine which relies on the text associated with the pictures — and not on the images themselves. So the results are sometimes unsatisfactory. But this soon might change because engineers from UC San Diego (UCSD) have developed new algorithms to improve automated image labeling. It’s interesting to note that one of the researchers spent six months at Google using a cluster of 3,000 state-of-the-art Linux machines to refine the algorithms, based on what the team calls Supervised Multiclass Labeling (SML). The results obtained by this supervised trained system are pretty good, so it would not be surprising to see Google integrating this method soon.

Links: Primidi, ZDNet