Melanoma Detection using Deep Learning

Overview

This repository contains code for a melanoma detection project using deep learning techniques. Melanoma is a type of skin cancer, and early detection is crucial for effective treatment. The project aims to develop a reliable system for identifying melanoma from images using convolutional neural networks (CNNs) and advanced image processing techniques.

Project Structure

• data/: Directory containing the melanoma dataset.
• models/: Directory containing trained deep learning models.
• results/: Directory for storing evaluation results and metrics.
• src/: Source code directory containing Python scripts for model training, evaluation, and prediction.

Requirements

• Python 3.x
• TensorFlow
• Matplotlib
• scikit-learn
• NumPy
• seaborn

Usage

Data Preparation: Ensure the melanoma dataset is stored in the data/ directory. Model Training: Train the deep learning models by running the appropriate scripts in the src/ directory. Evaluation: Evaluate the trained models using the test dataset and analyze the results. Prediction: Use the trained models to predict melanoma from new images. Contributing Contributions to this project are welcome! Feel free to submit issues, feature requests, or pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

This project utilizes the TensorFlow library for deep learning. The melanoma dataset used in this project is sourced in the Repo only you can download from there.