# neupy.architectures.vgg16

neupy.architectures.vgg16()[source]

VGG16 network architecture with random parameters. Parameters can be loaded using neupy.storage module.

Originally VGG16 was built in order to solve image classification problem. It was used in the ImageNet competition. The goal of the competition is to build a model that classifies image into one of the 1,000 categories. Categories include animals, objects, transports and so on.

VGG16 has roughly 138 million parameters.

vgg19
VGG19 network
squeezenet
SqueezeNet network
resnet50
ResNet50 network

References

Very Deep Convolutional Networks for Large-Scale Image Recognition. https://arxiv.org/abs/1409.1556

Examples

>>> from neupy import architectures
>>> vgg16 = architectures.vgg16()
>>> vgg16
(?, 224, 224, 3) -> [... 41 layers ...] -> (?, 1000)

>>>
>>> from neupy import algorithms
>>> optimizer = algorithms.Momentum(vgg16, verbose=True)