inceptionresnetv2

Pretrained Inception-ResNet-v2 convolutional neural network

Description

Inception-ResNet-v2 is a convolutional neural network that is trained on more than a million images from the ImageNet database [1]. The network is 164 layers deep and can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many animals. As a result, the network has learned rich feature representations for a wide range of images. The network has an image input size of 299-by-299. For more pretrained networks in MATLAB®, see Pretrained Deep Neural Networks.

You can use classify to classify new images using the Inception-ResNet-v2 network. Follow the steps of Classify Image Using GoogLeNet and replace GoogLeNet with Inception-ResNet-v2.

To retrain the network on a new classification task, follow the steps of Train Deep Learning Network to Classify New Images and load Inception-ResNet-v2 instead of GoogLeNet.

example

net = inceptionresnetv2 returns a pretrained Inception-ResNet-v2 network.

This function requires the Deep Learning Toolbox™ Model for Inception-ResNet-v2 Network support package. If this support package is not installed, then the function provides a download link.

Examples

collapse all

Download and install the Deep Learning Toolbox Model for Inception-ResNet-v2 Network support package.

Type inceptionresnetv2 at the command line.

inceptionresnetv2

If the Deep Learning Toolbox Model for Inception-ResNet-v2 Network support package is not installed, then the function provides a link to the required support package in the Add-On Explorer. To install the support package, click the link, and then click Install. Check that the installation is successful by typing inceptionresnetv2 at the command line. If the required support package is installed, then the function returns a DAGNetwork object.

net = inceptionresnetv2
net = 

  DAGNetwork with properties:

         Layers: [825×1 nnet.cnn.layer.Layer]
    Connections: [922×2 table]

Output Arguments

collapse all

Pretrained Inception-ResNet-v2 convolutional neural network, returned as a DAGNetwork object.

References

[1] ImageNet. http://www.image-net.org

[2] Szegedy, Christian, Sergey Ioffe, Vincent Vanhoucke, and Alexander A. Alemi. "Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning." In AAAI, vol. 4, p. 12. 2017.

Introduced in R2017b