Algorithm 1 A Brief Pseudo Code Function for the NN Training
1:	////Output
2:	function [imds,layers,options] = Experiment1_setup1(params)
3:	/////Load Image Data
4:	dataFolder
5:	fullfile(‘C:\Users\H738\Desktop\XXXS\Experiment1\CH7_1\TEST’);
6:	imds = imageDatastore(dataFolder, …
7:	if ‘IncludeSubfolders’,true, …
8:	‘LabelSource’,‘foldernames’);
9:	numTrainingFiles = 0.1;
10:	[imds,imdsValidation] = splitEachLabel(imds,numTrainingFiles);
11:	endif
12:	////Define Network Architecture
13:	switch params.Network
14:	case “alexnet”
15:	load(‘AlexNet’,’layers_1’)
16:	///parameters announce
18:	(inputSize; imds; imdsValidation;imdsValidation);
19:	layers = layers_1;
20:	case“googlenet”
21:	load(‘GoogLeNet’,’lgraph_1’)
22:	///parameters announce
23:	(inputSize; imds; imdsValidation;imdsValidation);;
24:	layers = lgraph_1;
25:	case“resnet101”
26:	load(‘Resnet101’,’lgraph_2’)
27:	///parameters announce
28:	(inputSize; imds; imdsValidation;imdsValidation);;
29:	layers = lgraph_2;
30:	otherwise
31:	msg = [‘Undefined network selection.’ …
32:	‘Options are “default” and “googlenet” and “resnet101”.’];
33:	error(msg);
34:	end
35:	///Specify Training Options
36:	options = trainingOptions(params.Solver, …
37:	‘MiniBatchSize’,2280, …
38:	‘MaxEpochs’,50, …
39:	‘InitialLearnRate’,1 × 104, …
40:	‘Shuffle’,’every-epoch’, …
41:	‘ValidationData’,imdsValidation, …
42:	‘ValidationFrequency’,5, …
43:	‘ExecutionEnvironment’,“cpu”,…
	‘Verbose’,true, …
	‘plots’,‘training-progress’);