VGG-19
id:
vgg-19-181-11709694
title:
VGG-19
text:
The VGG models are a series of convolutional neural networks (CNNs) developed by the Visual Geometry Group (VGG) at the University of Oxford. They achieved state-of-the-art results in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) in 2014. It was historically important as an early influential model designed by composing generic modules, whereas AlexNet (2012) was designed "from scratch". The VGG family includes various configurations with different depths, denoted by the letter "
brand slug:
wiki
category slug:
encyclopedia
description:
Series of convolutional neural networks for image classification
original url:
https://en.wikipedia.org/wiki/VGG-19
date created:
2024-09-05T23:19:58Z
date modified:
2024-09-06T01:57:51Z
main entity:
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/0/00/VGG_module_architecture.svg","width":564,"height":489}
fields total:
13
integrity:
15