Closed-loop-optogenetics-KapurLab/adhocSequential.m at main · 50-Cent/Closed-loop-optogenetics-KapurLab · GitHub

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function layers = adhocSequential()

layers = [
    imageInputLayer([4096*4, 1, 1])

    convolution2dLayer([3,1],8,'Padding','same')
    batchNormalizationLayer
    reluLayer

    averagePooling2dLayer([2,1],'Stride',2)

    convolution2dLayer([3,1],16,'Padding','same')
    batchNormalizationLayer
    reluLayer

    averagePooling2dLayer([2,1],'Stride',2)

    convolution2dLayer([3,1], 32,'Padding','same')
    batchNormalizationLayer
    reluLayer

    averagePooling2dLayer([2,1],'Stride',2)

    convolution2dLayer([3,1],64,'Padding','same')
    batchNormalizationLayer
    reluLayer

    averagePooling2dLayer([2,1],'Stride',2)

    convolution2dLayer([3,1],128,'Padding','same')
    batchNormalizationLayer
    reluLayer

    maxPooling2dLayer([2,1],'Stride',2)

    convolution2dLayer([3,1],256,'Padding','same')
    batchNormalizationLayer
    reluLayer

    maxPooling2dLayer([2,1],'Stride',2)

    dropoutLayer(0.2)
    fullyConnectedLayer(1)
    regressionLayer];

end