Pretrained DenseNet-201 convolutional neural network
DenseNet-201 is a convolutional neural network that is trained on more than a million images from the ImageNet database . The network is 201 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.
To retrain the network on a new classification task, follow the steps of Train Deep Learning Network to Classify New Images and load DenseNet-201 instead of GoogLeNet.
Download and install the Deep Learning Toolbox Model for DenseNet-201 Network support package.
densenet201 at the command line.
If the Deep Learning
Toolbox Model for DenseNet-201 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
densenet201 at the command line. If the required support package
is installed, then the function returns a
ans = DAGNetwork with properties: Layers: [709×1 nnet.cnn.layer.Layer] Connections: [806×2 table]
 ImageNet. http://www.image-net.org
 Huang, Gao, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q. Weinberger. "Densely Connected Convolutional Networks." In CVPR, vol. 1, no. 2, p. 3. 2017.