CIFAR-10

Description

CIFAR-10 Dataset is an image classification dataset for the field of machine vision. It has 60,000 color images in 10 categories of aircraft, cars, birds, cats, deer, dogs, frogs, horses, boats and trucks, all of which are 32 * 32 in size. It contains 5 training batches and 1 test batch, each batch has 10,000 images.
The dataset was published in 2009 by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton of the Department of Computer Science at the University of Toronto, and is the subject of a paper called Learning Multiple Layers of Features from Tiny Images.

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