Baidaa Al-Bander b.al-bander@keele.ac.uk
Benchmarking of deep learning algorithms for skin cancer detection based on a hybrid framework of entropy and VIKOR techniques
AL-BANDER, BAIDAA; YAS, QAHTAN M.; MAHDI, HUSSAIN; AL-HAMD, RWAYDA KH.S.
Authors
QAHTAN M. YAS
HUSSAIN MAHDI
RWAYDA KH.S. AL-HAMD
Journal Article Type | Article |
---|---|
Acceptance Date | Aug 6, 2021 |
Publication Date | Oct 4, 2021 |
Journal | Turkish Journal of Electrical Engineering and Computer Sciences |
Print ISSN | 1300-0632 |
Publisher | Scientific and Technological Research Council of Turkey (TUBITAK) |
Peer Reviewed | Peer Reviewed |
Volume | 29 |
Issue | 1 |
Pages | 2634 - 2648 |
DOI | https://doi.org/10.3906/elk-2103-65 |
Files
Benchmarking of deep learning algorithms for skin cancer detectio.pdf
(653 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Real-Time Lumen Detection for Autonomous Colonoscopy
(2022)
Conference Proceeding
A Comparision of Node Detection Algorithms Over Wireless Sensor Network
(2022)
Journal Article
Attention Mechanism Guided Deep Regression Model for Acne Severity Grading
(2022)
Journal Article
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search