densenet201
DenseNet-201 convolutional neural network
Description
DenseNet-201 is a convolutional neural network that is 201 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®, seePretrained Deep Neural Networks.
You can useclassify
to classify new images using the DenseNet-201 model. Follow the steps ofClassify Image Using GoogLeNetand replace GoogLeNet with DenseNet-201.
To retrain the network on a new classification task, follow the steps ofTrain Deep Learning Network to Classify New Imagesand load DenseNet-201 instead of GoogLeNet.
returns a DenseNet-201 network trained on the ImageNet data set.net
= densenet201
This function requires the Deep Learning Toolbox™ Model for DenseNet-201 Network support package. If this support package is not installed, then the function provides a download link.
returns a DenseNet-201 network trained on the ImageNet data set. This syntax is equivalent tonet
= densenet201('Weights','imagenet'
)net = densenet201
.
returns the untrained DenseNet-201 network architecture. The untrained model does not require the support package.lgraph
= densenet201('Weights','none'
)
Examples
Output Arguments
References
[1]ImageNet. http://www.image-net.org
[2] Huang, Gao, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q. Weinberger. "Densely Connected Convolutional Networks." InCVPR, vol. 1, no. 2, p. 3. 2017.