Skin Cancer Lesions Classification Using Deep Learning Techniques


Authors : Dr. R. Srinivasa Rao; N. Gopi Rajesh; P. Sai Aashritha; P. Keerthi; P. Sharon Kiran

Volume/Issue : Volume 8 - 2023, Issue 3 - March

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://bit.ly/42Sy59U

DOI : https://doi.org/10.5281/zenodo.7789099

Abstract : According to World Health Organization, one of the most prevalent types of cancer is skin cancer of human malignancy. Skin Cancer is more likely to be cured and treated more inexpensively if detected early. Melanoma, the deadliest variety of skin cancer, can manifest itself in a variety of ways. Early melanoma detection can increase the number of people who survive the disease. The main contributor to the development of skin cancer is sun exposure (ultraviolet). In this article, a variety of deep learning algorithms for skin cancer detection are introduced. The aim of this essay is to give a newbie a better understanding of the various methods for spotting skin cancer.

Keywords : Skin Cancer, Melanoma, Human Malignancy, Deep Learning.

According to World Health Organization, one of the most prevalent types of cancer is skin cancer of human malignancy. Skin Cancer is more likely to be cured and treated more inexpensively if detected early. Melanoma, the deadliest variety of skin cancer, can manifest itself in a variety of ways. Early melanoma detection can increase the number of people who survive the disease. The main contributor to the development of skin cancer is sun exposure (ultraviolet). In this article, a variety of deep learning algorithms for skin cancer detection are introduced. The aim of this essay is to give a newbie a better understanding of the various methods for spotting skin cancer.

Keywords : Skin Cancer, Melanoma, Human Malignancy, Deep Learning.

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe