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 is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

Automatic medical image segmentation is a crucial topic in the medical domain and
successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the …

Transformers have recently gained attention in the computer vision domain due to their
ability to model long-range dependencies. However, the self-attention mechanism, which is …

Convolutional neural networks (CNNs) have been the de facto standard in a diverse set of
computer vision tasks for many years. Especially, deep neural networks based on seminal …

Abstract Background and Objective: Although automated Skin Lesion Classification (SLC) is
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …

Melanoma is a serious skin disease. Automatic recognition of this lesion by dermoscopic
images is a difficult task. Recently, the deep learning paradigm has become a good …

In the past few years, convolutional neural networks (CNNs), particularly U-Net, have been
the prevailing technique in the medical image processing era. Specifically, the U-Net model …

A dual attention deep learning network is developed to classify three types of steel defects,
locate their positions, and depict their shapes on the steel surface in an automatic and …

Diabetic Retinopathy (DR) is a highly prevalent complication of diabetes mellitus, which
causes lesions on the retina that affect vision which may lead to blindness if it is not detected …