深度残差网络matlab代码
时间: 2023-09-14 17:02:37 浏览: 42
以下是一个简单的深度残差网络的 MATLAB 代码示例:
```matlab
% 定义网络结构
layers = [
imageInputLayer([32 32 3])
convolution2dLayer(3, 32, 'Padding', 'same')
batchNormalizationLayer
reluLayer
convolution2dLayer(3, 32, 'Padding', 'same')
batchNormalizationLayer
reluLayer
convolution2dLayer(3, 32, 'Padding', 'same')
batchNormalizationLayer
additionLayer(2)
reluLayer
convolution2dLayer(3, 64, 'Stride', 2, 'Padding', 'same')
batchNormalizationLayer
reluLayer
convolution2dLayer(3, 64, 'Padding', 'same')
batchNormalizationLayer
convolution2dLayer(3, 64, 'Padding', 'same')
batchNormalizationLayer
additionLayer(2)
reluLayer
convolution2dLayer(3, 128, 'Stride', 2, 'Padding', 'same')
batchNormalizationLayer
reluLayer
convolution2dLayer(3, 128, 'Padding', 'same')
batchNormalizationLayer
convolution2dLayer(3, 128, 'Padding', 'same')
batchNormalizationLayer
additionLayer(2)
reluLayer
averagePooling2dLayer(8)
fullyConnectedLayer(10)
softmaxLayer
classificationLayer];
% 加载数据集
[XTrain, YTrain, XTest, YTest] = LoadData();
% 训练网络
options = trainingOptions('sgdm', 'InitialLearnRate', 0.01, 'MaxEpochs', 20);
net = trainNetwork(XTrain, YTrain, layers, options);
% 测试网络
YPred = classify(net, XTest);
accuracy = sum(YPred == YTest) / numel(YTest);
disp(['Test accuracy: ' num2str(accuracy)]);
```
上述代码实现了一个包含三个残差块的深度残差网络,用于对 CIFAR-10 数据集进行分类。其中,`LoadData` 函数用于加载数据集,`trainingOptions` 函数用于设置训练选项。您可以根据您的需求进行修改和调整。
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