Classification of Skin Cancer empowered with convolutional neural network
Ayesha Atta, Muhammad Adnan Khan, Muhammad Asif, Ghassan F. Issa, Raed A. Said, Tauqeer Faiz
Abstract
Cancer is a major cause of death for many people around the world. There are a number of types of cancers and they are curable; only if it is detected at its early stages. Skin cancer has increasing victims all around the world. Many Computers based diagnoses have been developed to deal with this disease and help the physician to classify and detect the occurrence of the cancer. In this study, a reliable methodology has been proposed to deal with the lung's cancer classification based upon the data of 3600 pictures (224 x 224). There are two classes of images: Malignant and benign. Each class contains 1800 images. A reliable system is developed using a Convolutional Neural Network and fully connected layers. The proposed model improved the accuracy to 86.23% with efficient computations.