This repository contains a classification model made by Matlab for Diabetic Retinopathy Detection.
- For classification with 5 classes, I have installed a set of images from this Dataset (approximately 450MB).
- For classification with 3 classes, I used the same dataset as the previous one (with 5 classes). However, I combined "Mild nonproliferative diabetic retinopathy (NPDR)" and "Moderate NPDR" into 'Moderate', and "Severe NPDR" and "PDR" into 'Advanced'.
This model is built using a pretrained model 'AlexNet', along with 3 additional layers.
The model uses the following optimization algorithm:
- Adam ('adam') for training.
The training settings are as follows:
- Mini-batch size (MiniBatchSize): 32
- Maximum number of epochs (MaxEpochs): 10
- Initial learning rate (InitialLearnRate): 0.0001
- Validation frequency (ValidationFrequency): Calculated based on the number of training images
- Displaying
- The accuracy for the model with 5 classes: 62,14% .
- The accuracy for the model with 3 classes: 73,79% .
- The accuracy is not perfect but it is good, especialy for the 3 classes.
This repository is licensed under the MIT License.