CIFAR-10 Image Classification Dataset

CIFAR-10 Dataset is an image classification dataset for machine vision. It has 60,000 color images of 10 categories, including airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks. The size is 32*32. It contains 5 training batches and 1 test batch, each with 10,000 images.

The dataset was released in 2009 by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton from the Department of Computer Science at the University of Toronto. The related paper is "Learning Multiple Layers of Features from Tiny Images".