Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …

In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

Human activity recognition (HAR) has been of interest in recent years due to the growing
demands in many areas. Applications of HAR include healthcare systems to monitor …

In this paper, we present a method (Action-Fusion) for human action recognition from depth
maps and posture data using convolutional neural networks (CNNs). Two input descriptors …

Recent advances in artificial intelligence and machine learning (ML) led to effective methods
and tools for analyzing the human behavior. Human Activity Recognition (HAR) is one of the …

In this paper, we propose a novel approach for efficient training of deep neural networks in a
bottom-up fashion using a layered structure. Our algorithm, which we refer to as deep …

The self-regulated recognition of human activities from time-series smartphone sensor data
is a growing research area in smart and intelligent health care. Deep learning (DL) …

Human Activity Recognition (HAR) refers to an emerging area of interest for medical,
military, and security applications. However, the identification of the features to be used for …

Human activity recognition has become an important research topic within the field of
pervasive computing, ambient assistive living (AAL), robotics, health-care monitoring, and …

Numerous studies have been carried out in recent years on the recognition, tracking, and
discrimination of human activities. Automatic recognition of physical activities is often …