Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting
new knowledge. By using DL, the extraction of advanced data representations and …

High-speed networks are utilized to satisfy user demands by using cloud and edge services.
Due to the heterogeneous nature of these networks, security, trust, and privacy are the …

Abstract Acute Lymphoblastic Leukemia (ALL) is one of the most common types of cancer
globally, and the invasive tests used to diagnose it are costly and time-consuming …

Background Prevalence of dementia illness, causing certain morbidity and mortality globally,
places burden on global public health. This study primary goal was to assess future risks of …

With the increasing severity and frequency of cyberattacks, the rapid expansion of smart
objects intensifies cybersecurity threats. The vast communication traffic data between …

Background B-cell acute lymphoblastic leukemia (B-ALL) is one of the most widespread
cancers, and its definitive diagnosis demands invasive and costly diagnostic tests with side …

This study focuses on leveraging data-driven techniques to diagnose brain tumors through
magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we …

Background. In today's industrialized world, coronary artery disease (CAD) is one of the
leading causes of death, and early detection and timely intervention can prevent many of its …

Acute lymphoblastic leukemia (ALL) is a rare type of blood cancer caused due to the
overproduction of lymphocytes by the bone marrow in the human body. It is one of the …

One of the prevalent methods of image forgery is copy-move, where one or more regions of
an image are duplicated and moved elsewhere in the image. It is usually difficult to detect …