Fei-Fei Li, who argued from 2007 that models were starved of data rather than ideas and used crowdsourced labelling to reach roughly 14 million images across 20,000+ categories. The 2012 ILSVRC contest run on it is where AlexNet made deep learning mainstream.
Card 1 of 259. Answer: Fei-Fei Li, who argued from 2007 that models were starved of data rather than ideas and used crowdsourced labelling to reach roughly 14 million images across 20,000+ categories. The 2012 ILSVRC contest run on it is where AlexNet made deep learning mainstream.
About · Quizzes · History of AI · To suggest new questions or report an error send me a dm.
Fei-Fei Li conceived ImageNet and led the team that built it. ImageNet is a database of about 14.2 million images, each labeled with one of 21,841 noun categories taken from the WordNet hierarchy, built to give computer vision far more training data than any earlier dataset.
Li began working on the idea in 2006 and launched the project at Princeton in 2007 with computer scientist Kai Li, organizing the categories around WordNet after meeting WordNet researcher Christiane Fellbaum. Labeling that many images in a lab was impossible, so from 2008 to 2010 the team used Amazon Mechanical Turk, eventually drawing on about 49,000 workers in 167 countries. The first paper, led by PhD student Jia Deng, was only a poster at CVPR 2009.
Interviewers often mix up the full dataset with the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), which ran from 2010 to 2017 on a 1,000-class subset with about 1.28 million training images. AlexNet won the 2012 edition with a 15.3% top-5 error against 26.2% for the runner-up.
