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Pretrained Networks

Use pretrained image networks to quickly learn new tasks

Use transfer learning to take advantage of the knowledge provided by a pretrained network to learn new patterns in new image data. Fine-tuning a pretrained image classification network with transfer learning is typically much faster and easier than training from scratch. Using pretrained deep networks enables you to quickly create models for new tasks without defining and training a new network, having millions of images, or having a powerful GPU. To explore the pretrained networks available, use Deep Network Designer.

Apps

Deep Network DesignerDesign and visualize deep learning networks

Functions

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trainingOptionsOptions for training deep learning neural network
trainnetTrain deep learning neural network (Since R2023b)
testnetTest deep learning neural network (Since R2024b)
imagePretrainedNetworkPretrained neural network for images (Since R2024a)
predictCompute deep learning network output for inference
minibatchpredictMini-batched neural network prediction (Since R2024a)
scores2labelConvert prediction scores to labels (Since R2024a)
confusionchartCreate confusion matrix chart for classification problem
sortClassesSort classes of confusion matrix chart

Blocks

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PredictPredict responses using a trained deep learning neural network (Since R2020b)
Image ClassifierClassify data using a trained deep learning neural network (Since R2020b)

Topics

Featured Examples
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