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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.


Deep Network DesignerDesign and visualize deep learning networks


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trainingOptionsOptions for training deep learning neural network
trainnetTrain deep learning neural network (Seit R2023b)
analyzeNetworkAnalyze deep learning network architecture
imagePretrainedNetworkPretrained neural network for images (Seit R2024a)
predictCompute deep learning network output for inference (Seit R2019b)
minibatchpredictMini-batched neural network prediction (Seit R2024a)
scores2labelConvert prediction scores to labels (Seit R2024a)
confusionchartCreate confusion matrix chart for classification problem
sortClassesSort classes of confusion matrix chart


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