How to assign weights for layers while building novel image classification network using deep learning toolbox

How to assign weights for layers while building novel image classification network using deep learning toolbox

Answer 1

[Sai Pavan]

Hi Divya,

I understand that you are trying to know the process of assigning weights to layers when building an image classification model.

You can assign weights to layers by specifying the “Weights” property for each layer. The “Weights” property allows you to initialize the layer's weights with custom values or pretrained weights.

Please find the below code snippet that demonstrates the process of assigning weights to different layers of a network:

layers = [ 
    imageInputLayer([32 32 3]) 
    convolution2dLayer(3, 16, 'Weights', customWeights) % Specify custom weights for this layer 
    reluLayer() 
    fullyConnectedLayer(10, 'Weights', pretrainedWeights) % Specify pretrained weights for this layer 
    softmaxLayer() 
    classificationLayer() 
    ]; 
customWeights = randn([3 3 3 16]); % Example of custom weights for a convolutional layer 
pretrainedWeights = load('pretrained_weights.mat'); % Example of pretrained weights for a fully connected layer
net = trainNetwork(trainingData, layers, options); % Create and train the network 

Please refer to the below documentation to learn more about “Weights” property:

https://www.mathworks.com/help/deeplearning/ref/nnet.cnn.layer.convolution2dlayer.html?s_tid=doc_ta#:~:text=Weights%20%E2%80%94%20Layer%20weights

Hope it helps.

Regards,

Sai Pavan