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New Research Could Improve Google Image Search

New research recently published out of University of California – San Diego could allow Google’s Image Search to easily begin using elements from “true image search” — that is, the ability for software to detect and identify elements appearing within the image itself rather than just relying upon external text metadata to associate keywords with the images. Read on for more details.

 This new method is called “Supervised Multiclass Labeling (SML)”.  In an article published in the IEEE (Institute of Electrical and Electronics Engineers) Computer Society journal, TPAMI (Transactions on Pattern Analysis and Machine Intelligence) called “Supervised Learning of Semantic Classes for Image Annotation and Retrieval [1]“, researchers

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