Background: Skin cancer classificationusing convolutional neural networks (CNNs) proved
better results in classifying skin lesions compared with dermatologists which is lifesaving in …

Background Skin cancer is the most common cancer type affecting humans. Traditional skin
cancer diagnosis methods are costly, require a professional physician, and take time …

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 …

Coffee is an important export product of the tropical countries where it is grown. Therefore,
the separation of coffee beans in the world in terms of the quality element and variety forgery …

Many studies have recently used several deep learning methods for detecting skin cancer.
However, hyperspectral imaging (HSI) is a noninvasive optics system that can obtain …

Skin cancer is a type of dangerous disease, and early detection is necessary to increases
the survival rate. In recent years, deep learning models applied to computerized skin cancer …

Skin cancer is among the primary cancer types that manifest due to various dermatological
disorders, which may be further classified into several types based on morphological …

Skin cancer is one the most dangerous types of cancer and is one of the primary causes of
death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early …

Malignancy is the tendency of a medical condition to progressively become fatal and
generally refers to the presence of cancerous cells that can spread, invade, and destroy …

This paper presents a novel methodology for skin cancer diagnosis based on deep learning
and metaheuristics. The method combines a multi-level optimal thresholding segmentation …