Data: https://drive.google.com/drive/folders/1vOw-fa9QEGJHtiABa790eUYTvLX8TkQi?usp=sharing
Problem Statement: The goal of this project is to classify Chest X-ray images as normal(healthy) or Pneumonia cases using CNN, Pre-Trained Models & Vision Transformers and compare the results.
In deep learning, a convolutional neural network is a class of artificial neural network, most commonly applied to analyze visual imagery.
Vision Transformer (ViT) emerged as a competitive alternative to convolutional neural networks (CNNs) that are currently state-of-the-art in computer vision and widely used for different image recognition tasks.
Model Outputs:
| Model | Parameters Trained | Accuracy |
|---|---|---|
| CNN 2D | 2,008,193 | 72 |
| Pre-Trained - VGG16 | 15,935,809 | 91.4 |
| Vision Transformer | 85,842,179 | 72 |