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Review Article |

Skin Cancer Detection and Classification using Deep learning methods

Author(s): Anchal Kumari and Dr. Punam Rattan*

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 4

Publisher : FOREX Publication

Published : 30 November 2023

e-ISSN : 2347-470X

Page(s) : 1072-1086

DOI: https://doi.org/10.37391/ijeer.110427

Abstract

Skin cancer is a very dangerous disease that needs to be found early, so that it can be treated effectively. In the past few years, classifiers built on convolutional neural networks (CNNs) have become the best way to find melanoma. According to the review, the CNN-based classifier is as accurate as dermatologist in classifying skin cancer images, allowing for faster and more accurate detection. This article examines the most recent studies on Machine learning and deep learning-based melanoma categorization in depth. We provide a comprehensive description of the machine learning and deep learning classifier, including details on the accuracy of these classifiers. The primary objective of this research is to analyze and collect current research trends, issues, and opportunities for melanoma diagnosis, as well as to investigate the current approach for using deep learning to detect and recognize melanoma. The main finding of this review is that the neural network provides high accuracy as comparison to machine learning methods.

Keywords: Skin Lesion, Deep Learning, Ceroscopy, Classification, Neural Network, Melanoma.




Anchal Kumari, Research Scholar, Lovely Professional University, Jalandhar, Punjab India; Email: anchalsharma897@gmail.com

Dr. Punam Rattan*, Associate Professor, Lovely Professional University, Jalandhar, Punjab India; Email: punamrattan@gmail.com

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Anchal Kumari and Dr. Punam Rattan (2023), Skin Cancer Detection and Classification using Deep learning methods. IJEER 11(4), 1072-1086. DOI: 10.37391/ijeer.110427.