matlab lenet
时间: 2023-10-06 14:07:01 浏览: 42
LeNet is a convolutional neural network architecture that was developed by Yann LeCun in 1998 for handwritten digit recognition. It has since been widely used for image classification and other computer vision tasks.
In MATLAB, LeNet can be implemented using the Neural Network Toolbox. The toolbox provides a pre-trained LeNet model for digit recognition, which can be used directly or fine-tuned for other image classification tasks.
To use the pre-trained LeNet model for digit recognition, you can follow these steps:
1. Load the digit dataset using the following code:
```matlab
digitDatasetPath = fullfile(matlabroot,'toolbox','nnet','nndemos', ...
'nndatasets','DigitDataset');
digitData = imageDatastore(digitDatasetPath, ...
'IncludeSubfolders',true,'LabelSource','foldernames');
```
2. Split the dataset into training and validation sets:
```matlab
[trainDigitData,valDigitData] = splitEachLabel(digitData,0.7,'randomized');
```
3. Load the pre-trained LeNet model:
```matlab
net = alexnet;
```
4. Train the LeNet model on the digit dataset:
```matlab
options = trainingOptions('sgdm', ...
'InitialLearnRate',0.001, ...
'MaxEpochs',20, ...
'MiniBatchSize',64, ...
'ValidationData',valDigitData, ...
'ValidationFrequency',30, ...
'Plots','training-progress');
trainedNet = trainNetwork(trainDigitData,net,options);
```
5. Test the trained LeNet model on a new digit image:
```matlab
im = imread('digit3.png');
im = imresize(im,[227 227]);
label = classify(trainedNet,im);
```
Note that the above code assumes that the digit dataset is stored in the default location provided by the Neural Network Toolbox. If your dataset is stored elsewhere, you will need to modify the `digitDatasetPath` variable accordingly.