Search results
ImageNet is an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by hundreds and thousands of images. The project has been instrumental in advancing computer vision and deep learning research.
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3] .
Sep 17, 2019 · ImageNet is an ongoing research effort to provide researchers around the world with image data for training large-scale object recognition models. What is ImageNet? ImageNet is an image dataset organized according to the WordNet hierarchy.
The **ImageNet** dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.
Download ImageNet Data. The most highly-used subset of ImageNet is the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2012-2017 image classification and localization dataset. This dataset spans 1000 object classes and contains 1,281,167 training images, 50,000 validation images and 100,000 test images.
Oct 27, 2022 · ImageNet is the most popular dataset in computer vision research. The image dataset contains collected images for all sorts of categories found in the WordNet hierarchy. The 168 GB large dataset contains 1.3 million images separated into 1,000 classes with different grains of label resolution.
Jul 26, 2017 · What’s ImageNet? In the late 1980s, Princeton psychologist George Miller started a project called WordNet, with the aim of building a hierarchal structure for the English language. It would be...
Feb 11, 2024 · ImageNet is a publicly-available large-scale database with annotated images, composed to be used in multiple computer vision tasks. It contains over 14 million images, with each image annotated using WordNet synonym sets. It is one of the largest resources available for training deep learning models in image recognition tasks.
We introduce here a new database called “ImageNet”, a large-scale ontology of images built upon the backbone of the WordNet structure. ImageNet aims to populate the majority of the 80,000 synsets of WordNet with an average of 500–1000 clean and full resolution images.
ImageNetV2. The ImageNetV2 dataset contains new test data for the ImageNet benchmark. ImageNetV2 contains three test sets with 10,000 new images each. Importantly, these test sets were sampled after a decade of progress on the original ImageNet dataset.
