Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous
measurement of activities of daily living, making them especially well-suited for health …

Sign language recognition is often carried out using hierarchical classification approach to
reduce complexity and enhance accuracy. In this paper, mutli-label classification is …

Increasing interest in analyzing human gait using various wearable sensors, which is known
as Human Activity Recognition (HAR), can be found in recent research. Sensors such as …

Human activity recognition (HAR) is a classification process that is used for recognizing
human motions. A comprehensive review of currently considered approaches in each stage …

Human activity recognition (HAR) is the process of classifying a person's actions, and it is an
essential task for many human‐centered applications. Multi‐instance learning (MIL) is a …

Human activity recognition (HAR) has become ubiquitous in modern daily life, and thus
requires robust classification algorithms. Accelerometers are the most commonly used …

Human Activity Recognition (HAR) of everyday activities using smartphones has been
intensively researched over the past years. Despite the high detection performance …

Recently, smart home devices have been widely used to assist and facilitate the lives of
human beings. Human activity recognition (HAR) aims to identify human activities using …

Recognizing human daily activities with motion sensors data, specifically, modes of
locomotion and transportation provides important contextual information that enhances the …

Recognizing human activities from multi-channel time series data collected from wearable
sensors has become an important practical application of machine learning. A serious …