ImageNet is currently the world's largest image recognition database.It is mainly used for image classification and target detection in the field of machine vision. The dataset is organized according to the WordNet hierarchy, where each node (also called category) consists of hundreds or even thousands of images, and each node has an average of more than 500 images. The dataset contains a total of 22,000 image categories and about 15 million images.

The ImageNet Dataset was first released by Fei-Fei Li and others from Stanford University at the Society for Visual Science in 2009, and has been continuously improved in the ImageNet Visual Recognition Challenge (ILSVRC) since 2010.