A Deep Learning Framework for Early Detection of Skin Cancer: Implementing CNNs with Augmented Dermoscopic Images

Skin cancer, particularly melanoma, poses a significant global health risk due to rising cases, high mortality rates, and delayed detection. This project introduces an automated detection system using image processing and a CNN classifier to differentiate malignant from benign lesions. By employing data augmentation, feature extraction, and preprocessing techniques, the model enhances early diagnosis, enabling timely and life-saving interventions.