matlablenet
时间: 2023-10-06 14:07:11 浏览: 55
MatLab LeNet is a convolutional neural network (CNN) architecture that was introduced by Yann LeCun in 1998. It was specifically designed for handwritten digit recognition tasks. The LeNet architecture consists of two convolutional layers, followed by two fully connected layers, and the final output layer.
In MatLab, you can implement the LeNet architecture using the Neural Network Toolbox. This toolbox provides functions and tools to design, train, and validate neural networks. To implement LeNet, you would need to define the architecture layers, set up the training parameters, and then train the network using a set of labeled images.
Here is an example code snippet that shows how to implement LeNet in MatLab:
```matlab
layers = [
imageInputLayer([28 28 1])
convolution2dLayer(5, 6)
reluLayer
maxPooling2dLayer(2, 'Stride', 2)
convolution2dLayer(5, 16)
reluLayer
maxPooling2dLayer(2, 'Stride', 2)
fullyConnectedLayer(120)
reluLayer
fullyConnectedLayer(84)
reluLayer
fullyConnectedLayer(10)
softmaxLayer
classificationLayer
];
options = trainingOptions('adam', ...
'MaxEpochs', 10, ...
'InitialLearnRate', 0.001);
net = trainNetwork(trainingImages, trainingLabels, layers, options);
```
Please note that this is just a basic example and you may need to modify the code based on your specific requirements and dataset.
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