Video-based human activity recognition (HAR) is an important task in many fields, such as
healthcare monitoring, video surveillance, and sports analysis. This review paper aims to …

Utilizing data acquired by multiple wearable sensors can usually guarantee more accurate
recognition for deep learning based human activity recognition. However, an increased …

Human activity recognition (HAR) is an essential task in many applications such as health
monitoring, rehabilitation, and sports training. Sensor-based HAR has received increasing …

Wearable exoskeleton robots have become a promising technology for supporting human
motions in multiple tasks. Activity recognition in real-time provides useful information to …

Human Activity Recognition (HAR) has gained significant attention due to its broad range of
applications, such as healthcare, industrial work safety, activity assistance, and driver …

The less training data and insufficient supervision limit the performance of the deep
supervised models for brain disease diagnosis. It is significant to construct a learning …

Convolutional neural networks (CNNs) have shown great promise in human activity
recognition (HAR), but long-term dependencies in time series data can be difficult to capture …

Type 2 diabetes (T2D) is a worldwide chronic disease that is difficult to cure and causes a
heavy social burden. Early prediction of T2D can effectively identify high-risk populations …

Abstract The Internet of Things (IoT), cloud computing, and machine learning opened an
opportunity for new smart systems. These technologies have triggered huge traffic and delay …

The more detailed and accurate earth observation has been made driven by the progress of
satellites and sensors optical photography technology, which poses both an opportunity and …