• Thejashree H K
• Dr.G. F. Ali Ahammed

Skin malignancy is the most widely recognized sort of disease, which affects the life of people every year. The detection of skin disease in the beginning periods is a difficult and costly procedure. Having an automated technique for melanoma identification will help dermatologists in the early analysis of this kind of skin malignancy. In the last few years, significant advancements have taken place in the domain of computer vision. With the advent of new algorithms, it has become possible to differentiate between clinically similar skin conditions. In this paper, a technique for detecting skin lesion images into Malignant and Benign categories is implemented by utilizing Convolutional Neural Networks (CNNs). The Convolutional Neural Network is trained to detect the injuries to a high level of exactness.

Keywords: Malignant, Benign, Computer Vision, Convolutional Neural Networks.

"Melanoma Detection using Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.318-321, June-2019, Available :http://www.jetir.org/papers/JETIR1906C52.pdf

"Melanoma Detection using Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp318-321, June-2019, Available at : http://www.jetir.org/papers/JETIR1906C52.pdf