主要内容

efficientnetb0

EfficientNet-b0 convolutional neural network

所有的页面崩溃
  • EfficientNet-b0 network architecture

Syntax

net = efficientnetb0
net = efficientnetb0('Weights','imagenet')
lgraph = efficientnetb0('Weights','none')

Description

EfficientNet-b0 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 EfficientNet-b0 model. Follow the steps ofClassify Image Using GoogLeNetand replace GoogLeNet with EfficientNet-b0.

To retrain the network on a new classification task, follow the steps ofTrain Deep Learning Network to Classify New Imagesand load EfficientNet-b0 instead of GoogLeNet.

example

net= efficientnetb0returns an EfficientNet-b0 model network trained on the ImageNet data set.

This function requires the Deep Learning Toolbox™ ModelEfficientNet-b0网络support package. If this support package is not installed, then the function provides a download link.

net= efficientnetb0('Weights','imagenet')returns a EfficientNet-b0 model network trained on the ImageNet data set. This syntax is equivalent tonet = efficientnetb0.

lgraph= efficientnetb0('Weights','none')returns the untrained EfficientNet-b0 model network architecture. The untrained model does not require the support package.

Examples

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Download and install the Deep Learning Toolbox ModelEfficientNet-b0网络support package.

Typeefficientnetb0at the command line.

efficientnetb0

If the Deep Learning Toolbox ModelEfficientNet-b0网络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 clickInstall. Check that the installation is successful by typingefficientnetb0at the command line. If the required support package is installed, then the function returns aDAGNetworkobject.

efficientnetb0
ans = DAGNetwork with properties: Layers: [290×1 nnet.cnn.layer.Layer] Connections: [363×2 table] InputNames: {'ImageInput'} OutputNames: {'classification'}

Visualize the network using Deep Network Designer.

deepNetworkDesigner(efficientnetb0)

Explore other 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.

Output Arguments

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Pretrained EfficientNet-b0 convolutional neural network, returned as aDAGNetworkobject.

Untrained EfficientNet-b0 convolutional neural network architecture, returned as aLayerGraphobject.

References

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

[2] Mingxing Tan and Quoc V. Le, “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,”ArXiv Preprint ArXiv:1905.1194, 2019.

Extended Capabilities

Version History

Introduced in R2020b

See Also

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