A Critical Literature Review on Computer Vision Based Melanoma Detection and Identification

International Journal of Electrical and Electronics Engineering

© 2022 by SSRG - IJEEE Journal

Volume 9 Issue 12

Year of Publication : 2022

Authors : Soumya Gadag, P. Pradeepa

10.14445/23488379/IJEEE-V9I12P106

How to Cite?

Soumya Gadag, P. Pradeepa, "A Critical Literature Review on Computer Vision Based Melanoma Detection and Identification," SSRG International Journal of Electrical and Electronics Engineering, vol. 9,  no. 12, pp. 59-80, 2022. Crossref, https://doi.org/10.14445/23488379/IJEEE-V9I12P106

Abstract:

Melanoma is a skin tumor that initiates in the melanocyte cells that manage the pigmentation of the skin. Melanoma is still the most destructive form of skin cancer. In recent times, Convolutional neural network (CNN) centered classifiers have become quite popular for detecting melanoma. According to studies, CNN-based classifiers are equally accurate in classifying skin cancer scans as dermatologists. It has eased the process of Melanoma diagnoses. This work thoroughly assesses the most recent studies on the categorization of melanoma using deep learning and conventional machine learning procedures. The key purpose of this research is to compile cutting-edge research that identifies current research trends, problems, and prospects for melanoma diagnosis. It also looks into current approaches for applying deep learning to diagnose and identify melanoma. Finally, models, issues, and prospects have been provided to guide researchers working in the area of melanoma detection.

Keywords:

Melanoma, Skin cancer.

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