garreysingh asked . 2021-04-15

Add variable as input parameter in deep learning model

I am working on CNN model which increases pixel value of input image by x times. Here, the value of x is different for each pixel, which can be managed by CNN. I also want the value of x to be decided differently based on another variable. However, CNN model only takes image as input.
How can I add another additional variable with image as input for CNN model?

deep learning , matlab , simulink ,

Expert Answer

Kshitij Singh answered . 2024-12-21 18:06:00

You can refer to Multiple-Input and Multiple-Output Networks to create a network with multiple inputs.
The following is an example:
 
%% Define muliple input network.
layers1 = [
    imageInputLayer([28 28 3],'Name','input')  
    convolution2dLayer(3,3,'Padding','same','Name','conv_1')
    multiplicationLayer(2,'Name','mul')
    regressionLayer('Name','regression')];

lgraph = layerGraph(layers1);

layers2 = [imageInputLayer([28 28 3],'Name','x')];

lgraph = addLayers(lgraph,layers2);
% Connect layers.
lgraph = connectLayers(lgraph,'x','mul/in2');
% Analyze network.
analyzeNetwork(lgraph)
You can refer to  List of Deep Learning Layers for the available layers and Deep Learning Custom Layers to create a custom layer for your problem.
 


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