fyp_vad

Navigate to your repository folder

cd D:\ProjectFYP\fyp_vad

Create README.md file

@"

VaD Classification Models

This repository contains models for detecting and classifying Vascular Dementia from MRI scans.

Models

• binary_epoch50.h5: Binary classification model (VaD vs. Non-VaD)

  • Architecture: VGG16
  • Accuracy: 96%
  • Input shape: (224, 224, 3)

• VGG16_4_real_subclass.h5: Subtype classification model

  • Architecture: VGG16
  • Accuracy: 86.39%
  • Classes: Binswanger, Hemorrhagic, Strategic, Subcortical
  • Input shape: (128, 128, 3)

Usage

These models are designed to be used with TensorFlow/Keras:

```python import tensorflow as tf

Load binary model

binary_model = tf.keras.models.load_model('binary_epoch50.h5')

Load subclass model

subclass_model = tf.keras.models.load_model('VGG16_4_real_subclass.h5') ``` "@ | Out-File -FilePath "README.md" -Encoding utf8

Add and commit the README

git add README.md git commit -m "Add model documentation" git push