Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Abstract Body Sensor Networks (BSNs) have emerged as a revolutionary technology in
many application domains in health-care, fitness, smart cities, and many other compelling …

In this paper, we explore a novel model reusing task tailored for graph neural networks
(GNNs), termed as" deep graph reprogramming". We strive to reprogram a pre-trained GNN …

Human action recognition has a wide range of applications including biometrics,
surveillance, and human computer interaction. The use of multimodal sensors for human …

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at
empowering people's capabilities by means of digital environments that are sensitive …

A number of review or survey articles have previously appeared on human action
recognition where either vision sensors or inertial sensors are used individually …

Techniques from sparse signal representation are beginning to see significant impact in
computer vision, often on nontraditional applications where the goal is not just to obtain a …

Many ubiquitous computing applications involve human activity recognition based on
wearable sensors. Although this problem has been studied for a decade, there are a limited …

Sensor-based motion recognition integrates the emerging area of wearable sensors with
novel machine learning techniques to make sense of low-level sensor data and provide rich …

Abstract In Artificial Intelligence, Human Activity Recognition (HAR) refers to the capability of
machines to identify various activities performed by the users. The knowledge acquired from …