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预训练网络

使用预训练图像网络快速学习新任务

使用迁移学习以利用预训练网络所提供的知识来学习新图像数据中的新模式。通常来说，使用迁移学习对预训练的图像分类网络进行微调比从头开始训练更快更容易。使用预训练的深度网络，您可以针对新任务快速创建模型，而无需定义和训练新网络，也不需要使用数百万个图像或强大的 GPU。要探索可用的预训练网络，请使用深度网络设计器。

App

深度网络设计器设计、可视化和训练深度学习网络

函数

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trainingOptionsOptions for training deep learning neural network
trainNetworkTrain deep learning neural network
analyzeNetworkAnalyze deep learning network architecture
squeezenetSqueezeNet convolutional neural network
googlenetGoogLeNet 卷积神经网络
inceptionv3Inception-v3 convolutional neural network
densenet201DenseNet-201 convolutional neural network
mobilenetv2MobileNet-v2 convolutional neural network
resnet18ResNet-18 convolutional neural network
resnet50ResNet-50 卷积神经网络
resnet101ResNet-101 convolutional neural network
xceptionXception convolutional neural network
inceptionresnetv2Pretrained Inception-ResNet-v2 convolutional neural network
nasnetlargePretrained NASNet-Large convolutional neural network
nasnetmobilePretrained NASNet-Mobile convolutional neural network
shufflenetPretrained ShuffleNet convolutional neural network
darknet19DarkNet-19 convolutional neural network
darknet53DarkNet-53 convolutional neural network
efficientnetb0EfficientNet-b0 convolutional neural network
alexnetAlexNet 卷积神经网络
vgg16VGG-16 convolutional neural network
vgg19VGG-19 convolutional neural network
classifyClassify data using trained deep learning neural network
predictPredict responses using trained deep learning neural network
activations计算深度学习网络层激活
confusionchartCreate confusion matrix chart for classification problem
sortClassesSort classes of confusion matrix chart

模块

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PredictPredict responses using a trained deep learning neural network
Image Classifier使用经过训练的深度学习神经网络对数据进行分类

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