Improved skin cancer detection using CNN

Juveriya Shaikh; Rubeena Khan; Yashwant Ingle; Nuzhat Shaikh

doi:10.53730/ijhs.v6nS2.8762

Authors

Juveriya Shaikh
juveriyash05@gmail.com
Modern Education Society’s College of Engineering, Pune
Rubeena Khan Modern Education Society’s College of Engineering, Pune
Yashwant Ingle Modern Education Society’s College of Engineering, Pune
Nuzhat Shaikh Modern Education Society’s College of Engineering, Pune

Keywords:

image segmentation, convolutional neural network, skin cancer

Abstract

Pollution, an unhealthy lifestyle, UV radiation, and other factors can contribute to skin cancer. A variety of machine learning techniques have been developed in the past to detect such malignancies before they worsen. The goal of this article is to utilize a convolutional neural network to segment skin lesion images. The purpose of this study is to see how deep learning may be utilized to segment skin lesion photos. People may discover what skin diseases they may have, how to protect themselves from it, and what measures they can take early on to successfully treat the disease using Artificial Intelligence. Machine learning may be used to diagnose the problem and help us predict the result. The most widely used classification technology is the support vector machine. The discoveries might help doctors treat sickness early on and avoid further deterioration.

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