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

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Muhammad
Muhammad 2022-11-15
评论： Ayush 2022-11-22
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';

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