how to implement CBAM with a pretarined network in matlab. i have seen tutorials doing this on other platforms but not on matlab.

%this is the code i found on GitHub but couldn't implement it

lgraph = layerGraph();

tempLayers = imageInputLayer([227 227 3],"Name","imageinput");

lgraph = addLayers(lgraph,tempLayers);

tempLayers = maxPooling2dLayer([5 5],"Name","maxpool_1","Padding","same");

lgraph = addLayers(lgraph,tempLayers);

tempLayers = averagePooling2dLayer([5 5],"Name","avgpool2d_1","Padding","same");

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

multiplicationLayer(2,"Name","multiplication_1")

fullyConnectedLayer(10,"Name","fc_1")

fullyConnectedLayer(10,"Name","fc_2")

fullyConnectedLayer(10,"Name","fc_3")

leakyReluLayer(0.01,"Name","leakyrelu_1")];

lgraph = addLayers(lgraph,tempLayers);

tempLayers = averagePooling2dLayer([5 5],"Name","avgpool2d_2","Padding","same");

lgraph = addLayers(lgraph,tempLayers);

tempLayers = maxPooling2dLayer([5 5],"Name","maxpool_2","Padding","same");

lgraph = addLayers(lgraph,tempLayers);

tempLayers = [

multiplicationLayer(2,"Name","multiplication_2")

leakyReluLayer(0.01,"Name","leakyrelu_2")

sigmoidLayer("Name","sigmoid")

yolov2OutputLayer([16 16;32 32],"Name","yolov2-out")];

lgraph = addLayers(lgraph,tempLayers);

% 清理辅助变量

clear tempLayers;

%链接所有层

lgraph = connectLayers(lgraph,"imageinput","maxpool_1");

lgraph = connectLayers(lgraph,"imageinput","avgpool2d_1");

lgraph = connectLayers(lgraph,"maxpool_1","multiplication_1/in2");

lgraph = connectLayers(lgraph,"avgpool2d_1","multiplication_1/in1");

lgraph = connectLayers(lgraph,"leakyrelu_1","avgpool2d_2");

lgraph = connectLayers(lgraph,"leakyrelu_1","maxpool_2");

lgraph = connectLayers(lgraph,"avgpool2d_2","multiplication_2/in1");

lgraph = connectLayers(lgraph,"maxpool_2","multiplication_2/in2");

0 comments on commit b93ff1d

[Tian,HCong]

Hello, have you resolved your problem now? I am also very interested in this problem.

[Laraib]

No i was not able to resolve it. Though my fellow implemented it but using tensorflow and python. In matlab, I couldn't do it.