Modern computer vision algorithms are based on convolutional neural networks (CNNs),
and both end-to-end learning and transfer learning modes have been used with CNN for …

Due to the wide availability of easy-to-access content on social media, along with the
advanced tools and inexpensive computing infrastructure, has made it very easy for people …

The accurate and rapid detection of brain tumors is crucial for expediting patient
rehabilitation and saving lives. Brain tumors exhibit considerable variation in size, shape …

Deep learning-based approaches have garnered a great deal of interest among different
methods in structural health monitoring (SHM), whose primary objective is to assess …

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment
process and helps to save the lives of a large number of people worldwide. Because they …

Researchers are increasingly interested in leveraging the Internet of Things in medical and
healthcare systems to provide better solutions such as remote health monitoring, personal …

In hospitals and pathology, observing the features and locations of brain tumors in Magnetic
Resonance Images (MRI) is a crucial task for assisting medical professionals in both …

Previously, the brain tumour segmentation is carried out as the manual process for detecting
the brain tumour from the huge quantity of Medical Resonance Images (MRI) that is obtained …

Brain tumors (BT) present a considerable global health concern because of their high
mortality rates across diverse age groups. A delay in diagnosing BT can lead to death …

Brain tumors are one of the most threatening diseases to human health. Accurate
identification of the type of brain tumor is essential for patients and doctors. An automated …