Multi-Model Deep Learning System for Screening Human Monkeypox Using Skin Images

Abstract

sion dataset. Results: By amalgamating features extracted from all three CNNs and utilizing the medium Gaussian kernel of the SVM classifier, our proposed system achieves an outstanding av- erage classification accuracy of 90.4%. Conclusions: Our developed MPXCN-Net is suitable for test- ing with a large diversified dataset before being used in clin- ical settings.