A Comparative Study Of CNN And SVM With Particle Swarm Optimization For Skin Cancer Detection In CT Images
Dr. R. Vijay Arumugam, S. Senthamizhselvi · International Journal of Environmental Sciences · 2025
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.