CNN+BILSTM Architecture

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Mohanad Alkhodari
Mohanad Alkhodari on 17 Jul 2020
Commented: Asvin Kumar on 3 Aug 2020
Hello
Could someone please let me know if my implmentation of CNN+BILSTM network is correct? Am not getting good performance:
I am trying to classify 12-Lead ECG signals
inputSize = [1250 12 1];
numHiddenUnits = 10;
layers = [ ...
sequenceInputLayer(inputSize,'Name','input','normalization','none')
sequenceFoldingLayer('Name','fold')
convolution2dLayer([21 1],16,'Name','conv1','Padding','same')
maxPooling2dLayer([7 1],'Stride',7,'Name','maxpool1','Padding','same')
convolution2dLayer([17 1],32,'Name','conv2','Padding','same')
maxPooling2dLayer([6 1],'Stride',6,'Name','maxpool2','Padding','same')
convolution2dLayer([13 1],64,'Name','conv3','Padding','same')
maxPooling2dLayer([7 1],'Stride',7,'Name','maxpool3','Padding','same')
sequenceUnfoldingLayer('Name','unfold')
flattenLayer('Name','flatten')
bilstmLayer(numHiddenUnits,'OutputMode','last','Name','bilstm1')
fullyConnectedLayer(numClasses, 'Name','fc')
softmaxLayer('Name','softmax')
classificationLayer('Name','classification')];
Thank you
  1 Comment
Asvin Kumar
Asvin Kumar on 3 Aug 2020
If you are referring to any paper or material, providing that as a reference would help anyone from the community validate or make suggestions if that's what you're looking for.

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