define the resnet-18 network in matlab

Here is the code to define ResNet-18 in Matlab using the Deep Learning Toolbox:

main.m
% Load the pretrained ResNet-18 network
net = resnet18;

% View the network architecture 
analyzeNetwork(net)

% Modify the last layer to have 10 classes
numClasses = 10;
lgraph = layerGraph(net);
newLayers = fullyConnectedLayer(numClasses,'Name','new_fc');
lgraph = replaceLayer(lgraph,'fc1000',newLayers);

% Freeze all the layers except the last fully connected layer
layers = lgraph.Layers;
connections = lgraph.Connections;

for i = 1:numel(layers)
    if ismember('fc1000', layers(i).Name)
        break
    end
end

layers(1:i-1) = freezeWeights(layers(1:i-1));

% Define the training options
options = trainingOptions('sgdm');

% Train the network
imdsTrain = imageDatastore('training_images');
augimdsTrain = augmentedImageDatastore([224 224 3],imdsTrain);
netTrained = trainNetwork(augimdsTrain,layers,options);
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Note that in this example, we modified the last layer to have 10 classes (change numClasses to fit your use case) and froze all the layers except the last fully connected layer, which can help speed up training. Finally, we defined training options and trained the network on some training images.

Keep in mind that training ResNet-18 from scratch may require a lot of computational resources and time.

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