Skin Cancer Classification Using Convolutional Neural Networks

Skin Cancer Classification Using Convolutional  Neural Networks

^[1] Ms. Nischitha H, ^[2] Mrs. Geetha M

^[1]Student, Department of MCA, Bapuji Insititute of Enginnering and Technology, Davangere.

^[2] Assistant Professor, Department of MCA, Bapuji Institute of Engineering and Technology, Davangere.

Abstract: There is a necessary need for early     detection of skin cancer and can prevent further spread in some cases of skin cancers, such as melanoma and focal cell carcinoma. Anyhow there are several factors that have bad impacts on the detection accuracy. In Recent times, the use of image processing and machine vision in the field of healthcare and medical applications is increasing at a greater phase. In this paper, we are using the Convolution neural networks to detect and classify the class of cancer based on historical data of clinical images using CNN.Some of our objectives through this research are ,to build a CNN model to detect skin cancer with an accuracy of

>80% ,to keep the false negativity rate in the prediction to below 10%, to reach the precision of above 80% and do visualization on our Data. Simulation results show that the proposed method has superiority towards the other compared methods.

keywords: Skin cancer diagnosis, Deep learning, Convolutional neural networks [Standard CNN],Skin cancer, Artificial neural networks.