The world population is growing very fast and the lifestyle of human beings is changing with
time and place. So, there is a need for disease management which includes disease …

In recent years, there has been growing interest in the use of computer-assisted technology
for early detection of skin cancer through the analysis of dermatoscopic images. However …

This study introduces a new and inventive approach designed to address the complex
challenges encountered in the domain of image super-resolution (SR) tasks based on deep …

Deep learning models, particularly transformers and convolutional neural networks (CNNs),
have been commonly used to achieve high classification accuracy for image data. Since …

Rich details in an image are constantly vital for medical image analysis to detect a broad
extent of medical ailments. The diagnosis will be best served if the image is accessible in …

The precise and prompt identification of skin cancer is essential for efficient treatment.
Variations in colour within skin lesions are critical signs of malignancy; however …

Skin cancer (SC) is a common disease caused due to ultraviolet radiation. Accurate SC
detection is degraded due to some artifacts such as lesion variations in shape, size, color …

Objective To develop an explainable lightweight skin disease high-precision classification
model that can be deployed to the mobile terminal. Methods In this study, we present HI …

The medical sciences are facing a major problem with the auto-detection of disease due to
the fast growth in population density. Intelligent systems assist medical professionals in early …

Skin cancer is the most commonly found kind of cancer with eight diagnostic classes, which
makes its classification highly challenging. Recent years have witnessed the increased …