Hello, Can you please let me know how to create an attention layer for deep learning classification networks?

I am working on gestational age predicticon. I am using resnet for training the model and wants to add attention map for the feture extraction on specific region.

For example, this is my current network, which is from this example:

clear all

close all

imds = imageDatastore("F:\test\axial", ...

'IncludeSubfolders',true,'LabelSource','foldernames');

[imdsTrain,imdsValidation] = splitEachLabel(imds,0.7,'randomize'); %70% for train 30% for test

net=googlenet; % for the first time,you have to download the package from Add-on explorer

%Replace Final Layers

numClasses = numel(categories(imdsTrain.Labels));

lgraph = layerGraph(net);

newFCLayer = fullyConnectedLayer(numClasses,'Name','new_fc','WeightLearnRateFactor',10,'BiasLearnRateFactor',10);

lgraph = replaceLayer(lgraph,'loss3-classifier' ,newFCLayer);

newClassLayer = classificationLayer('Name','new_classoutput');

lgraph = replaceLayer(lgraph,'output',newClassLayer);

%Train Network

inputSize = net.Layers(1).InputSize;

augimdsTrain = augmentedImageDatastore(inputSize(1:2),imdsTrain);

augimdsValidation = augmentedImageDatastore(inputSize(1:2),imdsValidation);

options = trainingOptions('sgdm', ...

'MiniBatchSize',10, ...

'MaxEpochs',20, ...

'InitialLearnRate',1e-3, ...

'Shuffle','every-epoch', ...

'ValidationData',augimdsValidation, ...

'ValidationFrequency',5, ...

'Verbose',false, ...

'Plots','training-progress');

trainedNet = trainNetwork(augimdsTrain,lgraph,options);

YPred = classify(trainedNet,augimdsValidation);

accuracy = mean(YPred == imdsValidation.Labels)

C = confusionmat(imdsValidation.Labels,YPred)

cm = confusionchart(imdsValidation.Labels,YPred);

cm.Title = 'Confusion Matrix for Validation Data';

cm.ColumnSummary = 'column-normalized';

cm.RowSummary = 'row-normalized';

[Ayush]

@Muhammad kindly check this link.