Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

<Previous Article In Volume
Next Article In Volume>

Skin Aware: Early Skin Cancer Detection Using DeepLearning

Authors
Challawar Vaishnavi1, *, Kundelaraju Yadav1, Alle Harshavardhan1, Sama Sudheer Reddy1
1Department of CSE (Artificial Intelligence and Machine Learning), Institute of Aeronautical Engineering, Hyderabad, India
*Corresponding author. Email: 22955A6619@iare.ac.in
Corresponding Author
Challawar Vaishnavi
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_19How to use a DOI?
Keywords
Skin Cancer Detection; Deep Learning; MobileNet; CNN; Image Processing; AI in Healthcare
Abstract

Skin cancer is a critical global health issue that requires early and accurate detection for effective treatment. This project introduces Skin Guard, an AI-powered cancer detection system designed to classify skin conditions into seven categories, including malignant melanoma, basal cell carcinoma, and benign lesions. The system employs a Mobile Net-based Convolutional Neural Network (CNN), trained on the comprehensive HAM10000 dataset, to analyze medical images and provide precise classifications. The model’s performance is evaluated using key metrics such as accuracy, sensitivity, specificity, and categorical accuracy, demonstrating its robustness and reliability in distinguishing between various skin conditions. The integration of Mobile Net and HAM10000 ensures high diagnostic accuracy, minimizing false positives and negatives. Skin Guard offers a valuable tool for dermatologists, enabling timely and accurate diagnoses, ultimately improving patient outcomes and advancing skin cancer detection in clinical settings.

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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_19How 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  - Challawar Vaishnavi
AU  - Kundelaraju Yadav
AU  - Alle Harshavardhan
AU  - Sama Sudheer Reddy
PY  - 2025
DA  - 2025/11/04
TI  - Skin Aware: Early Skin Cancer Detection Using DeepLearning
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 204
EP  - 213
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_19
DO  - 10.2991/978-94-6463-858-5_19
ID  - Vaishnavi2025
ER  -