In recent years, an enormous amount of research has been carried out on support vector
machines (SVMs) and their application in several fields of science. SVMs are one of the …

Skin cancer is one of the most prevalent and deadly types of cancer. Dermatologists
diagnose this disease primarily visually. Multiclass skin cancer classification is challenging …

Simple Summary This paper proposes a deep learning-based skin cancer classification
network (DSCC_Net) that is based on a convolutional neural network (CNN) and …

Automated skin lesion classification in dermoscopy images is an essential way to improve
the diagnostic performance and reduce melanoma deaths. Although deep convolutional …

Background and objective Computer automated diagnosis of various skin lesions through
medical dermoscopy images remains a challenging task. Methods In this work, we propose …

Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

Automatic melanoma detection from dermoscopic skin samples is a very challenging task.
However, using a deep learning approach as a machine vision tool can overcome some …

Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

Background: State-of-the-art classifiers based on convolutional neural networks (CNNs)
were shown to classify images of skin cancer on par with dermatologists and could enable …

Skin Cancer accounts for one-third of all diagnosed cancers worldwide. The prevalence of
skin cancers have been rising over the past decades. In recent years, use of dermoscopy …