Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)

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Early Detection of Melanoma Through Dermoscopic Image Classification Using Deep Learning Techniques

Authors
T. M. Amirthalakshmi1, *, R. S. Keshav1, V. Sridharshan1, Hemachandran1
1SRM University, Ramapuram, Chennai, India
*Corresponding author.
Corresponding Author
T. M. Amirthalakshmi
Available Online 30 June 2025.
DOI
10.2991/978-94-6463-754-0_8How to use a DOI?
Keywords
Automated Skin Lesion Classification System; Early Melanoma Detection; Convolutional Neural Networks (CNNs); Dermoscopic Images; Data Augmentation; Machine Learning Integration
Abstract

This project introduces an Automated Skin Lesion Classification System aimed at improving early melanoma detection through advanced machine learning techniques. The system utilizes custom CNN architecture for analyzing dermoscopic images, leveraging Python-based tools like Augmentor for data augmentation and class imbalance handling. Key features include convolutional layers, pooling, and dropout layers, ensuring accurate feature extraction and overfitting prevention. A dataset of 2,357 images from ISIC was employed, achieving 84% validation accuracy. This innovation reduces diagnostic times significantly, offering near real-time insights to support dermatologists in making faster and more precise decisions, ultimately enhancing healthcare outcomes.

Copyright
© 2025 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.

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Volume Title
Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
Series
Atlantis Highlights in Engineering
Publication Date
30 June 2025
ISBN
978-94-6463-754-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-754-0_8How to use a DOI?
Copyright
© 2025 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

risenwbib
TY  - CONF
AU  - T. M. Amirthalakshmi
AU  - R. S. Keshav
AU  - V. Sridharshan
AU  - Hemachandran
PY  - 2025
DA  - 2025/06/30
TI  - Early Detection of Melanoma Through Dermoscopic Image Classification Using Deep Learning Techniques
BT  - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
PB  - Atlantis Press
SP  - 73
EP  - 80
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-754-0_8
DO  - 10.2991/978-94-6463-754-0_8
ID  - Amirthalakshmi2025
ER  -