This repository contains a MATLAB script for classifying medical images using various deep learning algorithms, including CNN, DNN, RNN, and ResNet-50. The script uses MATLAB's Deep Learning Toolbox and Image Processing Toolbox to preprocess the images, build and train the networks, and evaluate their performance.
- User Interface for Image Selection: Allows the user to select an image file using a graphical interface.
- Data Preprocessing: Handles image data loading, resizing, and augmentation.
- Convolutional Neural Network (CNN): Implements a CNN with multiple convolutional and pooling layers, followed by fully connected layers for image classification.
- Deep Neural Network (DNN): Implements a simple DNN with fully connected layers and ReLU activations for classification.
- Recurrent Neural Network (RNN): Utilizes a sequence input and LSTM layers for image classification.
- ResNet-50: Implements a simplified version of ResNet-50 architecture for more accurate image classification.
- Performance Evaluation: Evaluates and prints the accuracy of each network on the training and validation datasets.
- Visualization: Displays the input image and its predicted class using each model.
https://docs.google.com/document/d/1FjHNc9Y3fqSkxrKUHkCUh87uzkEtFDopJQLMx0vUrfo/edit?usp=sharing