Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Skin Cancer Detection using VGG-16

Breadcrumb

  • Home
  • Skin Cancer Detection using VGG-16

Dilruba Shareen 1, 2, * and Nazia Hossain 3

1 Department of Computer Science and Engineering, Khulna University of Engineering and Technology (KUET), Khulna, Bangladesh.
2 Department of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh.
3 Centre for Smart Analytics, Federation University Australia, Victoria, Australia.
 
Research Article
World Journal of Advanced Research and Reviews, 2024, 24(02), 2930-2937
Article DOI: 10.30574/wjarr.2024.24.2.3520
DOI url: https://doi.org/10.30574/wjarr.2024.24.2.3520
 
Received on 07 October 2024; revised on 23 November 2024; accepted on 28 November 2024
 
The recent increase in the prevalence of skin cancer, along with its significant impact on individuals’ lives, has garnered the attention of many researchers in the field of deep learning models, especially following the promising results observed using these models in the medical field. This study aimed to develop a system that can accurately diagnose one of three types of skin cancer: basal cell carcinoma (BCC), melanoma (MEL), and nevi (NV). Additionally, it emphasizes the importance of image quality, as many studies focus on the quantity of images used in deep learning. In this study, transfer learning was employed using the pre-trained VGG-16 model alongside a dataset sourced from Kaggle. 
Skin cancer; Deep learning; Basal cell carcinoma (BCC); Melanoma (MEL); Nevi (NV), Dermoscopic images; VGG-16
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-3520.pdf

Preview Article PDF

Dilruba Shareen and Nazia Hossain. Skin Cancer Detection using VGG-16. World Journal of Advanced Research and Reviews, 2024, 24(2), 2930-2937. Article DOI: https://doi.org/10.30574/wjarr.2024.24.2.3520

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.

All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 World Journal of Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution