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RESNET50

ResNet-50 convolutional neural network

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  • Resnet-50体系结构

Syntax

网= Resnet50
网= Resnet50('Weights','imagenet')
lgraph = resnet50('Weights','none')

Description

ResNet-50 is a convolutional neural network that is 50 layers deep. You can load a pretrained version of the network trained on more than a million images from the ImageNet database[1]。The pretrained 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®, see预处理的深神经网络。

You can use分类to classify new images using the ResNet-50 model. Follow the steps ofClassify Image Using GoogLeNetand replace GoogLeNet with ResNet-50.

To retrain the network on a new classification task, follow the steps ofTrain Deep Learning Network to Classify New Imagesand load ResNet-50 instead of GoogLeNet.

Tip

To create an untrained residual network suitable for image classification tasks, use重新植物。

example

网= Resnet50returns a ResNet-50 network trained on the ImageNet data set.

This function requires the Deep Learning Toolbox™ Modelfor ResNet-50 Networksupport package. If this support package is not installed, then the function provides a download link.

网= Resnet50('Weights','imagenet')returns a ResNet-50 network trained on the ImageNet data set. This syntax is equivalent to网= Resnet50。

lgraph= Resnet50('Weights','none')returns the untrained ResNet-50 network architecture. The untrained model does not require the support package.

Examples

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Download and install the Deep Learning Toolbox Modelfor ResNet-50 Networksupport package.

TypeRESNET50at the command line.

RESNET50

If the Deep Learning Toolbox Modelfor ResNet-50 Network万博1manbetx未安装支持软件包，然后该功能提供了指向附加探索器中所需的支持软件包的链接。要安装支持包，请单击链接，然后万博1manbetx单击Install。通过键入检查安装成功RESNET50at the command line. If the required support package is installed, then the function returns aDAGNetwork目的。

RESNET50
ans = DAGNetwork with properties: Layers: [177×1 nnet.cnn.layer.Layer] Connections: [192×2 table]

Visualize the network using Deep Network Designer.

DeepNetworkDesigner（Resnet50）

通过单击深度网络设计师中的其他预验证的网络新的。

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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预验证的Resnet-50卷积神经网络，作为一个DAGNetwork目的。

Untrained ResNet-50 convolutional neural network architecture, returned as aLayerGraph目的。

参考

[1]ImageNet。http://www.image-net.org

[2] He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. "Deep residual learning for image recognition." InIEEE计算机视觉和模式识别会议论文集，第770-778页。2016。

Extended Capabilities

版本历史

Introduced in R2017b

See Also

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