Accurate Deep Learning Algorithms for Skin Lesion Classification

A skin lesion is any irregularity or alteration to the texture, color, or appearance of the skin.It arises from a number of skin illnesses, such as malignancies, autoimmune diseases, allergies, and infections.Early detection and precise diagnosis of skin lesions are crucial for effective treatment and management of these disorders.Dermatologists and other healthcare professionals have traditionally diagnosed skin lesions through visual inspection.However, using this approach might result in a delayed or incorrect diagnosis.Skin lesion categorization accuracy has significantly improved as a result of recent advancements in deep learning techniques.This study looks at the different deep learning techniques used to classify skin lesions.These include transfer learning (DenseNet201 and ResNet52V2) and Convolutional Neural Networks (CNNs).Our study's results show that test images have a 91% accuracy rate, while training images have a 95% accuracy rate.