Skin Cancer Classification Using CNN

Author(s)	Manusree Reddirouthu, Akhila Manga, Vijaya Lakshmi Sattar
Country	India
Abstract	This paper introduces a system for early skin cancer detection and classification based on deep learning using Convolutional Neural Networks (CNNs). The system detects four types of skin cancers—melanoma, squamous cell carcinoma, nevus pigmentosus, and dermatofibroma—along with the differentiation between healthy and cancerous tissues. The system provides an accuracy of 94%, using image processing methods, several convolutional layers, and Adam optimization to provide effective and timely diagnosis. This strategy decreases the load on healthcare practitioners and favors early treatment, enhancing patient outcomes.
Keywords	Adam Optimizer, TensorFlow, CV2, Feature Extraction, CNN
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-21
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.43814
Short DOI	https://doi.org/g9mh7v

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International Journal For Multidisciplinary Research