CIFAR-100 Image Classification Dataset

CIFAR-100 Dataset is an image classification dataset used in the field of machine vision. It has 20 major categories and a total of 100 minor categories. Each minor category contains 600 images (500 training images and 100 test images) and each image has a small label and a large label.

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".