Pretrained Xception convolutional neural network
Xception is a convolutional neural network that is trained on more than a million images from the ImageNet database . The network is 71 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.
To retrain the network on a new classification task, follow the steps of Train Deep Learning Network to Classify New Images and load Xception instead of GoogLeNet.
Download and install the Deep Learning Toolbox Model for Xception Network support package.
xception at the command line.
If the Deep Learning
Toolbox Model for Xception 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
xception at the command line. If the required support package is
installed, then the function returns a
ans = DAGNetwork with properties: Layers: [171×1 nnet.cnn.layer.Layer] Connections: [182×2 table]
 ImageNet. http://www.image-net.org
 Chollet, F., 2017. "Xception: Deep Learning with Depthwise Separable Convolutions." arXiv preprint, pp.1610-02357.
Usage notes and limitations:
For code generation, you can load the network by using the syntax
xception or by passing the
xception function to
coder.loadDeepLearningNetwork. For example: