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nasnetmobile

Pretrained NASNet-Mobile convolutional neural network

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  • NASNet-Mobile network architecture

Syntax

net = nasnetmobile

Description

NASNet-Mobile is a convolutional neural network that is trained on more than a million images from the ImageNet database[1]. The network 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 224-by-224. For more pretrained networks in MATLAB®, seePretrained Deep Neural Networks.

You can useclassifyto classify new images using the NASNet-Mobile model. Follow the steps ofClassify Image Using GoogLeNetand replace GoogLeNet with NASNet-Mobile.

To retrain the network on a new classification task, follow the steps ofTrain Deep Learning Network to Classify New Imagesand load NASNet-Mobile instead of GoogLeNet.

example

net= nasnetmobilereturns a pretrained NASNet-Mobile convolutional neural network.

This function requires theDeep Learning Toolbox™ Model for NASNet-Mobile Networksupport package. If this support package is not installed, then the function provides a download link.

Examples

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Download and install theDeep Learning Toolbox Model for NASNet-Mobile Networksupport package.

Typenasnetmobileat the command line.

nasnetmobile

If theDeep Learning Toolbox Model for NASNet-Mobile Networksupport 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 clickInstall. Check that the installation is successful by typingnasnetmobileat the command line. If the required support package is installed, then the function returns aDAGNetworkobject.

nasnetmobile
ans = DAGNetwork with properties: Layers: [914×1 nnet.cnn.layer.Layer] Connections: [1073×2 table]

Visualize the network using Deep Network Designer.

deepNetworkDesigner(nasnetmobile)

探索其他r pretrained networks in Deep Network Designer by clickingNew.

Deep Network Designer start page showing available pretrained networks

If you need to download a network, pause on the desired network and clickInstallto open the Add-On Explorer.

You can use transfer learning to retrain the network to classify a new set of images.

Open the exampleTrain Deep Learning Network to Classify New Images. The original example uses the GoogLeNet pretrained network. To perform transfer learning using a different network, load your desired pretrained network and follow the steps in the example.

Load the NASNet-Mobile network instead of GoogLeNet.

net = nasnetmobile

Follow the remaining steps in the example to retrain your network. You must replace the last learnable layer and the classification layer in your network with new layers for training. The example shows you how to find which layers to replace.

Output Arguments

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Pretrained NASNet-Mobile convolutional neural network, returned as aDAGNetworkobject.

References

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

[2] Zoph, Barret, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le. "Learning Transferable Architectures for Scalable Image Recognition ."arXiv preprint arXiv:1707.070122, no. 6 (2017).

Extended Capabilities

See Also

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Topics

Introduced in R2019a

Deep Learning Toolbox Documentation

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