Performance Analysis of Deep Learning Algorithms in Skin Lesion Classification

As a malignant form of skin disease, skin carcinoma requires early identification and treatment. Development, implementation, and calibration of an advanced deep learning model for automated classification of skin types in multiple categories of lesions are the main objective. In the proposed approach, Convolutional Neural Network (CNN) models are utilized that efficiently extract pertinent information from the input images. The objective of this research work includes developing a CNN model with a detection accuracy of >80% for skin cancer, lowering the false negative rate to below 10
^%
, achieving a precision of >80%, and performing data visualization. The ResNet model combined with the VGGNet achieved an accuracy of 87% for the detection.