Overview
ImageNet is an extensive image database organized according to the WordNet hierarchy, primarily focusing on nouns. Each node in the hierarchy represents a synset, which is depicted by hundreds or thousands of images. With over 14 million images and 21,841 synsets, ImageNet serves as a crucial resource for training and evaluating computer vision models. The project has been instrumental in propelling advancements in deep learning, particularly in image recognition, object detection, and image classification tasks. ImageNet is freely available to researchers for non-commercial use, enabling them to develop and test new algorithms and methodologies in the field of artificial intelligence. The database is maintained and updated by Stanford Vision Lab, Stanford University, and Princeton University.