Question regarding designing a CNN structure

Dear

I am trying to design a CNN structure for a specific image input size. The structure I have tried to follow(just for my practice) is following:

imS = [1 23];
layers = [
    imageInputLayer(imS)
    
    convolution2dLayer(1,4,'Padding','same')
    batchNormalizationLayer
    reluLayer
    
    maxPooling2dLayer(2,'Stride',2)
    
    convolution2dLayer(1,8,'Padding','same')
    batchNormalizationLayer
    reluLayer
    
    maxPooling2dLayer(2,'Stride',2)
    
    convolution2dLayer(1,16,'Padding','same')
    batchNormalizationLayer
    reluLayer
    
    dropoutLayer(0.25)
    fullyConnectedLayer(10)
    
    softmaxLayer
    classificationLayer]

But during run time, the structure fails. And the following error is displaying:

Invalid network.
 Layer 5: Input size mismatch. Size of input to this layer is different from the expected input size.
    Inputs to this layer:
        from layer 4 (1×17×4 output)

Would you please highlight how to design a structure in this regard. My feelings is that I need to change the number of filters of the cnn according to the image size. Is there any thumb of rule/any general idea available to design a cnn structure based on the image size?

thanks,

[Javid Hamdard]

Check your input image size, and also your image input layer size it should to be same.