ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
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CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
SKIN CANCER DETECTION USING DL HYBRID CNN BASED
Authors
GLORY.R , SOORIYAKUMAR.R , SRINIVASAN.V , SUDHARSAN.D , SUDHARSHAN.V.P
Keywords
Skin Cancer Detection, Deep Learning, Transfer Learning, Convolutional Neural Networks, Medical Image Analysis, HAM10000 Dataset
Abstract
This paper is about a web application that uses deep learning to detect and classify skin lesions. The application uses a kind of dataset called the HAM10000 dataset, which has a lot of pictures of skin lesions. The system uses something called transfer learning and a new way of combining parts of the system to get better results.
The model is made up of two parts: one part is a -trained ResNet50 and the other part is a custom Convolutional Neural Network. These two parts work together to get an understanding of the skin lesions. The system is very good at classifying the skin lesions with a validation accuracy of 91.2% and an F1-score of 91.7%.
The system is made to be used by dermatologists to help them diagnose skin lesions. It is a web application. It is easy to use and can be used in real-time. This work shows that deep learning can be very helpful in medical image analysis and it can be used to make a tool to help healthcare practitioners.
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IJCRT — journal style
"SKIN CANCER DETECTION USING DL HYBRID CNN BASED", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.k950-k954, April 2026, Available :https://ijcrt.org/papers/IJCRT26A4270.pdf
APA — 7th edition
GLORY.R, SOORIYAKUMAR.R, SRINIVASAN.V, SUDHARSAN.D, & SUDHARSHAN.V.P. (2026). SKIN CANCER DETECTION USING DL HYBRID CNN BASED. International Journal of Creative Research Thoughts, 14(4), k950-k954. https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270
MLA — 9th edition
GLORY.R, et al. "SKIN CANCER DETECTION USING DL HYBRID CNN BASED." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. k950-k954, https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270.
Chicago — 17th, bibliography
GLORY.R, et al. "SKIN CANCER DETECTION USING DL HYBRID CNN BASED." International Journal of Creative Research Thoughts 14, no. 4 (2026): k950-k954. https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270.
Harvard — author–date
GLORY.R et al. (2026) 'SKIN CANCER DETECTION USING DL HYBRID CNN BASED', International Journal of Creative Research Thoughts, 14(4), pp. k950-k954. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270
IEEE — numbered reference
GLORY.R, SOORIYAKUMAR.R, SRINIVASAN.V, SUDHARSAN.D and SUDHARSHAN.V.P, "SKIN CANCER DETECTION USING DL HYBRID CNN BASED," IJCRT, vol. 14, no. 4, pp. k950-k954, Apr. 2026.
Vancouver — biomedical
GLORY.R, SOORIYAKUMAR.R, SRINIVASAN.V, SUDHARSAN.D, SUDHARSHAN.V.P. SKIN CANCER DETECTION USING DL HYBRID CNN BASED. IJCRT. 2026 Apr;14(4):k950-k954.
AMA — 11th edition
GLORY.R, SOORIYAKUMAR.R, SRINIVASAN.V, SUDHARSAN.D, SUDHARSHAN.V.P. SKIN CANCER DETECTION USING DL HYBRID CNN BASED. IJCRT. 2026;14(4):k950-k954. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT26A4270,
author = {GLORY.R and SOORIYAKUMAR.R and SRINIVASAN.V and SUDHARSAN.D and SUDHARSHAN.V.P},
title = {SKIN CANCER DETECTION USING DL HYBRID CNN BASED},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {k950-k954},
year = {2026},
month = {April},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - GLORY.R
AU - SOORIYAKUMAR.R
AU - SRINIVASAN.V
AU - SUDHARSAN.D
AU - SUDHARSHAN.V.P
TI - SKIN CANCER DETECTION USING DL HYBRID CNN BASED
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270
SP - k950-k954
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : k950-k954
Article Information
- Pages
- k950-k954
- Published
- April 2026
- Registration ID
- IJCRT_306874
- Published Paper ID
- IJCRT26A4270
- Research Area
- Health Science All
- Author Type
- Indian Author
- Location
- chengalpattu, Tamil Nadu, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 112
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4270
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT26A4270.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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