Human activity recognition is essential in many domains, including the medical and smart
home sectors. Using deep learning, we conduct a comprehensive survey of current state …

Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …

Deep convolutional neural networks (CNNs) achieve state-of-the-art performance in
wearable human activity recognition (HAR), which has become a new research trend in …

Human activity recognition (HAR) applications have received much attention due to their
necessary implementations in various domains, including Industry 5.0 applications such as …

Deep neural networks, including convolutional neural networks (CNNs), have been widely
adopted for human activity recognition in recent years. They have attained significant …

Nowadays, people use smart devices everywhere and for different applications such as
healthcare. The Internet of Healthcare Things (IoHT) generates enormous amounts of data …

In the era of smart life, tracking human activities and motion can play a significant role in the
advanced modern applications, such as the Internet of things (IoT), Internet of healthcare …

In the paper, we present a new dual attention method called DanHAR, which blends
channel and temporal attention on residual networks to improve feature representation …

Due to rapid development of sensor technology, human activity recognition (HAR) using
wearable inertial sensors has recently become a new research hotspot. Deep learning …

Efficiently identifying activities of daily living (ADL) provides very important contextual
information that is able to improve the effectiveness of various sports tracking and healthcare …