Built-In Pretrained Networks
Deep Learning Toolbox™ provides several pretrained networks suitable for transfer learning. Transfer learning is the process of taking a pretrained deep learning network and fine-tuning it to learn a new task. Using transfer learning is usually faster and easier than training a network from scratch. You can quickly transfer learned features to a new task using a smaller amount of data. To explore the available pretrained networks, use Deep Network Designer. For more information, see Pretrained Deep Neural Networks.
|Deep Network Designer||Design, visualize, and train deep learning networks|
|SqueezeNet convolutional neural network|
|GoogLeNet convolutional neural network|
|Inception-v3 convolutional neural network|
|DenseNet-201 convolutional neural network|
|MobileNet-v2 convolutional neural network (Since R2019a)|
|ResNet-18 convolutional neural network|
|ResNet-50 convolutional neural network|
|ResNet-101 convolutional neural network|
|Xception convolutional neural network (Since R2019a)|
|Pretrained Inception-ResNet-v2 convolutional neural network|
|Pretrained NASNet-Large convolutional neural network (Since R2019a)|
|Pretrained NASNet-Mobile convolutional neural network (Since R2019a)|
|Pretrained ShuffleNet convolutional neural network (Since R2019a)|
|DarkNet-19 convolutional neural network (Since R2020a)|
|DarkNet-53 convolutional neural network (Since R2020a)|
|EfficientNet-b0 convolutional neural network (Since R2020b)|
|AlexNet convolutional neural network|
|VGG-16 convolutional neural network|
|VGG-19 convolutional neural network|
- Classify Webcam Images Using Deep Learning
This example shows how to classify images from a webcam in real time using the pretrained deep convolutional neural network GoogLeNet.
- Train Deep Learning Network to Classify New Images
This example shows how to use transfer learning to retrain a convolutional neural network to classify a new set of images.
- Transfer Learning Using Pretrained Network
This example shows how to fine-tune a pretrained GoogLeNet convolutional neural network to perform classification on a new collection of images.
- Pretrained Deep Neural Networks
Learn how to download and use pretrained convolutional neural networks for classification, transfer learning and feature extraction.
- Deep Learning in MATLAB
Discover deep learning capabilities in MATLAB® using convolutional neural networks for classification and regression, including pretrained networks and transfer learning, and training on GPUs, CPUs, clusters, and clouds.
- Deep Learning Tips and Tricks
Learn how to improve the accuracy of deep learning networks.