Convolution Neural Network Models to Detect Melanoma: A Review
- DOI
- 10.2991/978-94-6463-094-7_37How to use a DOI?
- Keywords
- Melanoma; Convolution neural networks; Machine learning; Skin cancer detection
- Abstract
Skin cancer is one of the most serious health issues that humans face. Dermatologists face difficulty in making a skin cancer diagnosis because many skin cancer pigments seem alike. Early detection of skin cancers like Melanoma means a better chance of survival for the patient otherwise it can be life-threatening. For computer vision problems like image classification, deep learning has proven to be the state-of-the-art. There has been a great deal of research into the use of deep learning to automate skin cancer screening. The objective of this paper is to review the state-of-the-art CNN techniques used for Melanoma detection. This paper presents an overview of CNN, followed by analysing the existing work carried out in the area of Melanoma skin cancer detection using Convolution Neural Network (CNN).
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Naveen Palanichamy AU - R. Saravana Kumar AU - Su-Cheng Haw AU - Kok-Why Ng AU - Elham Anaam PY - 2022 DA - 2022/12/27 TI - Convolution Neural Network Models to Detect Melanoma: A Review BT - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022) PB - Atlantis Press SP - 469 EP - 479 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-094-7_37 DO - 10.2991/978-94-6463-094-7_37 ID - Palanichamy2022 ER -