Human activity recognition has gained importance in recent years due to its applications in
various fields such as health, security and surveillance, entertainment, and intelligent …

Human falls occur rarely; however, they can lead to severe consequences if not addressed
immediately. With the rise of nuclear families, there has been a significant increase in the …

In the new paradigm, learning using privileged information (LUPI) creates a more
informative strategy for tasks to achieve better prediction. SVM based methods including …

Human activity recognition has been a topic of attraction among researchers and developers
because of its enormous usage in widespread region of human life. The varied human …

In this paper, a multi-classification algorithm for human motion recognition based on Impulse-
Radio Ultra-wideband (IR-UWB) radar is presented. The algorithm includes three parts. First …

Deep learning architectures are being increasingly adopted for human activity recognition
using radar technology. A majority of these architectures are based on convolutional neural …

According to the real-living environment, radar-based human activity recognition (HAR) is
dedicated to recognizing and classifying a sequence of activities rather than individual …

Human Activity Recognition (HAR) is one of the essential building blocks of so many
applications like security, monitoring, the internet of things and human-robot interaction. The …

We propose an attention-augmented convolutional autoencoder for human activity
recognition using radar micro-Doppler signatures. We use attention to overcome the limited …

The recognition of individual activity has proven its importance in many application areas.
Even after the pandemic crisis worldwide, the remote monitoring of human actions and their …