Deep learning-based models have achieved significant success in detecting cardiac
arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the …

The field of automated lung cancer diagnosis using Computed Tomography (CT) scans has
been significantly advanced by the precise predictions offered by Convolutional Neural …

The exact lung cancer identification is a critical problem that has attracted the researchers'
attention. The practice of multiview single image and segmentation has been widely used for …

Abstract Human Activity Recognition (HAR) is an essential area of pervasive computing
deployed in numerous fields. In order to seamlessly capture human activities, various inertial …

Aging is inevitably associated with a decline in physical abilities and can pose challenges to
the social lives of elderly individuals. In long-term care facilities, group exercise is …

With mobile internet technology improving quickly, smartphones with many sensors have
become increasingly popular for detecting transportation modes. Transportation modes are …

Human activity recognition (HAR) is a crucial task in various applications, including
healthcare, fitness, and the military. Deep learning models have revolutionized HAR …

Depression and anxiety are prevalent mental illnesses that are frequently disregarded as
disorders. It is estimated that more than 5% of the population suffers from depression or …

The proposed work introduces a novel, lightweight feature fusion network model based on
the attention mechanism to address the issues of high time consumption and poor …

Numerous sensors on smart devices have made it possible to automatically recognize
human movement, which might be helpful for intelligent applications like elder care, smart …