Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in developing computer-aided diagnosis …

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 …

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 …

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 …

Melanoma is considered the most serious type of skin cancer. All over the world, the
mortality rate is much high for melanoma in contrast with other cancer. There are various …

Background and objective: Skin cancer is among the most common cancer types in the
white population and consequently computer aided methods for skin lesion classification …

Cancer is one of the leading causes of deaths in the last two decades. It is either diagnosed
malignant or benign–depending upon the severity of the infection and the current stage. The …

Skin cancer is a deadly disease, and its early diagnosis enhances the chances of survival.
Deep learning algorithms for skin cancer detection have become popular in recent years. A …

Malignant melanoma is one of the most aggressive forms of skin cancer. Early detection is
important as it significantly improves survival rates. Consequently, accurate discrimination of …

Melanoma remains the most harmful form of skin cancer. Convolutional neural network
(CNN) based classifiers have become the best choice for melanoma detection in the recent …