This project aims to develop a convolutional neural network (CNN) to classify seven types of skin lesion. The CNN will be incorporated into an Android application for remote diagnosis. The dataset used for training and validation is 10,015 detmatoscopic images (publicly available at https://www.kaggle.com/kmader/skin-cancer-mnist-ham10000).

The images are labelled with seven classifications: Actinic keratoses and intraepithelial carcinoma (akiec), basal cell carcinoma (bcc), benign keratosis-like lesions (bkl), dermatofibroma (df), melanoma (mel), melanocytic nevi (nv), and vascular lesions (vasc).