resnet18

Pretrained ResNet-18 convolutional neural network

ResNet-18 is a convolutional neural network that is trained on more than a million images from the ImageNet database [1]. The network is 18 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 224-by-224. For more pretrained networks in MATLAB®, see Pretrained Deep Neural Networks.

You can use classify to classify new images using the ResNet-18 model. Follow the steps of Classify Image Using GoogLeNet and replace GoogLeNet with ResNet-18.

To retrain the network on a new classification task, follow the steps of Train Deep Learning Network to Classify New Images and load ResNet-18 instead of GoogLeNet.

Syntax

net = resnet18

Description

example

net = resnet18 returns a pretrained ResNet-18 convolutional neural network.

This function requires the Deep Learning Toolbox™ Model for ResNet-18 Network support package. If this support package is not installed, then the function provides a download link.

Examples

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Download and install the Deep Learning Toolbox Model for ResNet-18 Network support package.

Type resnet18 at the command line.

resnet18

If the Deep Learning Toolbox Model for ResNet-18 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 resnet18 at the command line. If the required support package is installed, then the function returns a DAGNetwork object.

resnet18
ans = 

  DAGNetwork with properties:

         Layers: [72×1 nnet.cnn.layer.Layer]
    Connections: [79×2 table]

Output Arguments

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Pretrained ResNet-18 convolutional neural network, returned as a DAGNetwork object.

References

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

[2] He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. "Deep residual learning for image recognition." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770-778. 2016.

Introduced in R2018a