Human activity recognition using wearable sensors is an area of interest for various domains
like healthcare, surveillance etc. Various approaches have been used to solve the problem …

Human activity recognition (HAR) using smartphone sensors utilize time-series, multivariate
data to detect activities. Time-series data have inherent local dependency characteristics …

Human activities are inherently translation invariant and hierarchical. Human activity
recognition (HAR), a field that has garnered a lot of attention in recent years due to its high …

Traditional pattern recognition approaches have gained a lot of popularity. However, these
are largely dependent upon manual feature extraction, which makes the generalized model …

Abstract Various Human Activities are classified through time-series data generated by the
sensors of wearable devices. Many real-time scenarios such as Healthcare Surveillance …

Human Activity Recognition is a field concerned with the recognition of physical human
activities based on the interpretation of sensor data, including one-dimensional time series …

Human activity recognition has gained interest from the research community due to the
advancements in sensor technology and the improved machine learning algorithm …

The study of human regular tasks have become more prevalent and accessible as a result of
the widespread use of different sensors integrated into mobile devices. This issue now exists …

Human activity recognition and deep learning are two fields that have attracted attention in
recent years. The former due to its relevance in many application domains, such as ambient …

Nowadays, the most challenging and important problem of computer vision is to detect
human activities and recognize the same with temporal information from video data. The …