A Comparative Study Of CNN And SVM With Particle Swarm Optimization For Skin Cancer Detection In CT Images
Year: 2025
Type: article
Abstract: This research looks at how well deep learning and traditional machine learning methods can detect skin cancer using CT images. It uses a Convolutional Neural Network (CNN) to automatically extract features and classify images, while a Support Vector Machine (SVM) is fine-tuned with Particle Swarm Optimization (PSO) to improve its accuracy. The performance of both models is measured using Accuracy, Precision, Recall, F1-Score, and AUC-ROC. The results highlight the advantages and limitations of each method in terms of how accurately and efficiently they classify the images.
DOI: 10.64252/85js3c49
Authors: Dr. R. Vijay Arumugam, Dr. S. Senthamizhselvi
Institution: Government of Tamil Nadu
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411995745