From 5e5e1d02fe539d6d2b86b45d63aaa1497f11c931 Mon Sep 17 00:00:00 2001
From: psarlashkar <67120838+psarlashkar@users.noreply.github.com>
Date: Thu, 27 Aug 2020 08:50:08 -0500
Subject: [PATCH] Create densenet_3d_ageclassification.m

---
 densenet_3d_ageclassification.m | 83 +++++++++++++++++++++++++++++++++
 1 file changed, 83 insertions(+)
 create mode 100644 densenet_3d_ageclassification.m

diff --git a/densenet_3d_ageclassification.m b/densenet_3d_ageclassification.m
new file mode 100644
index 0000000..48a60aa
--- /dev/null
+++ b/densenet_3d_ageclassification.m
@@ -0,0 +1,83 @@
+% Create Layer Graph
+
+lgraph = layerGraph();
+%%
+n = 4; %this is the number of channels of the input image
+numClasses = 2; %this is the number of categories an image could be classified as (in example it was 3, for adult, 7-12, 3-5)
+%% Add Layer Branches
+% Add the branches of the network to the layer graph. Each branch is a linear 
+% array of layers.
+
+tempLayers = [
+    image3dInputLayer([64 64 64 4],"Name","input","Normalization","none")
+    batchNormalizationLayer("Name","BN_Module1_Level1")
+    convolution3dLayer([3 3 3],32,"Name","conv_Module1_Level1","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module1_Level1")];
+lgraph = addLayers(lgraph,tempLayers);
+
+tempLayers = [
+    batchNormalizationLayer("Name","BN_Module1_Level2")
+    convolution3dLayer([3 3 3],64,"Name","conv_Module1_Level2","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module1_Level2")];
+lgraph = addLayers(lgraph,tempLayers);
+
+tempLayers = [
+    concatenationLayer(4,2,"Name","depthcat_1")
+    maxPooling3dLayer([2 2 2],"Name","maxpool_Module1","Padding","same","Stride",[2 2 2])
+    batchNormalizationLayer("Name","BN_Module2_Level1")
+    convolution3dLayer([3 3 3],64,"Name","conv_Module2_Level1","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module2_Level1")];
+lgraph = addLayers(lgraph,tempLayers);
+
+tempLayers = [
+    batchNormalizationLayer("Name","BN_Module2_Level2")
+    convolution3dLayer([3 3 3],128,"Name","conv_Module2_Level2","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module2_Level2")];
+lgraph = addLayers(lgraph,tempLayers);
+
+tempLayers = [
+    concatenationLayer(4,2,"Name","depthcat_2")
+    maxPooling3dLayer([2 2 2],"Name","maxpool_Module2","Padding","same","Stride",[2 2 2])
+    batchNormalizationLayer("Name","BN_Module3_Level1")
+    convolution3dLayer([3 3 3],128,"Name","conv_Module3_Level1","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module3_Level1")];
+lgraph = addLayers(lgraph,tempLayers);
+
+tempLayers = [
+    batchNormalizationLayer("Name","BN_Module3_Level2")
+    convolution3dLayer([3 3 3],256,"Name","conv_Module3_Level2","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module3_Level2")];
+lgraph = addLayers(lgraph,tempLayers);
+
+tempLayers = [
+    concatenationLayer(4,2,"Name","depthcat_3")
+    maxPooling3dLayer([2 2 2],"Name","maxpool_Module3","Padding","same","Stride",[2 2 2])
+    batchNormalizationLayer("Name","BN_Module4_Level1")
+    convolution3dLayer([3 3 3],256,"Name","conv_Module4_Level1","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module4_Level1")
+    batchNormalizationLayer("Name","BN_Module4_Level2")
+    convolution3dLayer([3 3 3],512,"Name","conv_Module4_Level2","Padding","same","WeightsInitializer","narrow-normal")
+    reluLayer("Name","relu_Module4_Level2")
+    globalAveragePooling3dLayer("Name","pool5")
+    fullyConnectedLayer(numClasses,"Name","new_fc","BiasLearnRateFactor",10,"WeightLearnRateFactor",10)
+    softmaxLayer("Name","softmax")
+    classificationLayer("Name","new_classoutput")];
+lgraph = addLayers(lgraph,tempLayers);
+
+% clean up helper variable
+clear tempLayers;
+%% Connect Layer Branches
+% Connect all the branches of the network to create the network graph.
+
+lgraph = connectLayers(lgraph,"relu_Module1_Level1","BN_Module1_Level2");
+lgraph = connectLayers(lgraph,"relu_Module1_Level1","depthcat_1/in1");
+lgraph = connectLayers(lgraph,"relu_Module1_Level2","depthcat_1/in2");
+lgraph = connectLayers(lgraph,"relu_Module2_Level1","BN_Module2_Level2");
+lgraph = connectLayers(lgraph,"relu_Module2_Level1","depthcat_2/in1");
+lgraph = connectLayers(lgraph,"relu_Module2_Level2","depthcat_2/in2");
+lgraph = connectLayers(lgraph,"relu_Module3_Level1","BN_Module3_Level2");
+lgraph = connectLayers(lgraph,"relu_Module3_Level1","depthcat_3/in1");
+lgraph = connectLayers(lgraph,"relu_Module3_Level2","depthcat_3/in2");
+%% Plot Layers
+
+plot(lgraph);