neuralnet for calculating the percentage of the bluer image in matlab

To use a neural network to calculate the percentage of the bluer image, you need to first define the architecture of the neural network. You can use a simple feedforward neural network with one hidden layer.

Next, you need to prepare your data by creating a dataset of images with corresponding labels that indicate the percentage of the bluer image. You can do this by manually identifying the percentage of each image, or by using an image segmentation algorithm.

Once you have your dataset, you can train the neural network using the backpropagation algorithm. You will need to divide your data into a training set and a testing set, to ensure that your model does not overfit to the training data.

Here's a sample code snippet to get you started:

main.m
% Load your dataset
load('mydataset.mat');

% Define the architecture of your neural network
hiddenLayerSize = 10;
net = fitnet(hiddenLayerSize);

% Divide the dataset into training and testing sets
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the neural network
[net, tr] = train(net, X, Y);

% Test the neural network on a new image
I = imread('myimage.jpg');
percentage = net(I);
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