The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms.
[3] The 10 different classes represent airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks.
Since the images in CIFAR-10 are low-resolution (32x32), this dataset can allow researchers to quickly try different algorithms to see what works.
This is a table of some of the research papers that claim to have achieved state-of-the-art results on the CIFAR-10 dataset.
CIFAR-10 is also used as a performance benchmark for teams competing to run neural networks faster and cheaper.