validation accuracy not increasing

I want to increase the validation accuracy

This is my matlab code :

clear all

clc

outputFolder=fullfile('train/resized');

rootFolder=fullfile(outputFolder,'');

categories={'Mild DR 1','Moderate DR 2','No DR 0','Proliferative DR 4','Severe DR 3'};

%

imds=imageDatastore(fullfile(rootFolder,categories),'LabelSource','foldernames');

image_size =[224 224 3]

augimds = augmentedImageDatastore(image_size,imds)

tb1=countEachLabel(imds);

minSetcount=min(tb1{:,2});

imds =splitEachLabel(imds,minSetcount,'randomize');

[XTrain,YTrain] = splitEachLabel(imds, .5);

test_labels = imds.Labels;

tbl = numel(test_labels)

idx = randperm(size(XTrain.Labels,1),tbl/2);

Xtrain = string(XTrain.Labels(idx));

Ytrain = string(YTrain.Labels(idx));

XValidation = imageDatastore(fullfile(rootFolder,Xtrain),'LabelSource','foldernames');

YValidation =imageDatastore(fullfile(rootFolder,Ytrain),'LabelSource','foldernames');

Xaugvalidation = augmentedImageDatastore(image_size,XValidation);

Yaugvalidation = augmentedImageDatastore(image_size,YValidation);

net = network;

layers=[

imageInputLayer([224 224 3])

convolution2dLayer(24,8,'stride',1)

batchNormalizationLayer

clippedReluLayer(10)

maxPooling2dLayer(2,'Stride',2)

convolution2dLayer(12,16,'stride',1)

batchNormalizationLayer

clippedReluLayer(10)

maxPooling2dLayer(2,'Stride',2)

convolution2dLayer(6,32,'stride',1)

batchNormalizationLayer

clippedReluLayer(10)

maxPooling2dLayer(2,'Stride',2)

convolution2dLayer(3,64,'stride',1)

batchNormalizationLayer

clippedReluLayer(10)

maxPooling2dLayer(2,'Stride',2)

fullyConnectedLayer(5)

softmaxLayer

classificationLayer ];

options = trainingOptions('adam',....

'Shuffle','every-epoch',...

'MaxEpochs',100, ...

'ValidationData',{Xaugvalidation,Yaugvalidation}, ...

'Verbose',true,'ExecutionEnvironment' ,'gpu' ,...

'Plots','training-progress',...

'InitialLearnRate',.003)

net = trainNetwork(augimds,layers,options);

analyzeNetwork(net)

YPred = classify(net,imds);

accuracy = sum(YPred == test_labels)/numel(test_labels)*100;

for i=1:3

[file,path] = uigetfile('*.*');

if isequal(file,0)

disp('User selected Cancel');

else

disp(['User selected ', fullfile(path,file)]);

end

newImage = fullfile(path,file);

nimds = imageDatastore(newImage);

augimage = augmentedImageDatastore(image_size,nimds);

predicted_image = classify(net,augimage);

h=waitbar(1,sprintf("The loaded image belongs to %s class ",predicted_image));

newImage = imread(newImage);

Hard_exucates(newImage);

bloodVessels=VesselExtract( newImage);

figure;

imshow(bloodVessels);title('Extracted Blood Vessels');

end

[Cam Salzberger]

I would suggest more details on what you are trying to do, what products you are using, and what the issue is. See here for good suggestions.

[Image Analyst]

Looks normal, as expected. At some point, now matter how long it tries to tweak the weights, it just won't get any better. You can probably quit after 2 or 3 hundred iterations.

[utpal bhowmik]

so i don't get more than 90% validation accuracy ???