This repository contains the implementation of Convolutional Neural Networks (CNNs) for recognizing COVID-19 from medical images, developed by Mafizur Rahman on April 21, 2024.
The project applies deep learning techniques to detect the presence of COVID-19 in medical imagery. Three different CNN structures have been tested and evaluated to determine the most accurate model.
The dataset used in this project is the covidNetDataset
, which consists of medical images labeled as either "Positive" or "Negative" for the presence of COVID-19.
- Python
- TensorFlow
- Keras
- NumPy
- Matplotlib
- Seaborn
- scikit-learn
To run this project, first clone the repo on your device using the command below:
git clone https://github.com/yourusername/covid-recognition-cnn.git
## Models
The repository includes three different CNN architectures for you to explore. Each model's structure and performance metrics are documented within the notebook.
## Results
Evaluation metrics such as accuracy, precision, recall, F1 score, and confusion matrices for each model are available in the notebook for analysis.
## K-Fold Validation
K-Fold Cross-Validation is used to ensure the robustness of the models. The results are documented within the notebook.
## Contributing
If you'd like to contribute, please fork the repository and use a feature branch. Pull requests are warmly welcome.