Anomaly detection is a significant problem that has been studied in a broader spectrum of
research areas due to its diverse applications in different domains. Despite the usage of …

Skin cancer (melanoma and non-melanoma) is one of the most common cancer types and
leads to hundreds of thousands of yearly deaths worldwide. It manifests itself through …

Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …

Segmentation of skin lesions is a critical step in the process of skin lesion diagnosis. Such
segmentation is challenging due to the irregular shape, fuzzy contours and severe noise …

Cybersecurity in information technology (IT) infrastructures is one of the most significant and
complex issues of the digital era. Increases in network size and associated data have …

Automatic skin lesion segmentation is the most critical and relevant task in computer‐aided
skin cancer diagnosis. Methods based on convolutional neural networks (CNNs) are mainly …

Skin lesion segmentation is the first step in skin lesion assessment, and it can help with the
following classification task. It is a complex job because the borders of pigment regions may …

Melanoma is the least common skin cancer but the most severe and lethal. Due to the
expensive cost of medical screening, there is a need to develop automated computer-aided …

The generation of spectral libraries using hyperspectral data allows for the capture of
detailed spectral signatures, uncovering subtle variations in plant physiology, biochemistry …

Abstract Hybrid Fiber-Coaxial (HFC) networks are a popular infrastructure for delivering
internet to consumers, however, they are complex and susceptible to various errors. Internet …