Automated Skin Cancer Detection System

Skin cancer is one of the most common and potentially life-threatening types of cancer, but early detection significantly improves treatment outcomes. The Automated Skin Cancer Detection System leverages machine learning and computer vision techniques to analyze dermoscopic images of skin lesions and classify them as benign or malignant. The project involves preprocessing images, training a CNN model on labeled datasets, and validating its accuracy. The system aims to assist dermatologists in diagnosing skin cancer quickly and accurately, improving efficiency and reducing human error.

Basic Knowledge of Programming Languages like Python, R, TensorFlow etc.

Before Commencing the project the following links have to be examined.

https://www.isic-archive.com/

https://medium.com/

https://pyimagesearch.com/

https://github.com/