World’s Largest Image Database (ImageNet) to Help Computers Learn to See
While there are images all over the Internet, there are very few good ways of searching for them.
The way it works now is that you type in a word, and if you’re lucky and a person somewhere online has uploaded an image labeled with your search word, then you’ll see that image in your search results.
But what if the search engine didn’t have to rely on people labeling images correctly? What if the computer could just recognize images itself, the way people do?
To develop a system that can do that, Stanford computer scientist Fei-Fei Li created the world’s largest visual database, ImageNet, which holds 14 million labeled images.
A number of researchers have used the database to test their images as it developed over the last few years. This summer, when two Google researchers tested it they found it worked twice as well as other “neural networks,” or systems that try to mimic human brain functions.
About Gary Price
Gary Price (email@example.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.