Human activity recognition (HAR) is an emerging area of study and research field that
explores the development of automated systems to identify and categorize human activities …

Sensor-based human activity recognition (HAR), ie, the ability to discover human daily
activity patterns from wearable or embedded sensors, is a key enabler for many real-world …

Recent advances in deep learning have granted unrivaled performance to sensor-based
human activity recognition (HAR). However, in a real-world scenario, the HAR solution is …

Continual learning (CL), also known as lifelong learning, is an emerging research topic that
has been attracting increasing interest in the field of machine learning. With human activity …

Sensor-based human activity recognition (HAR), with the ability to recognise human
activities from wearable or embedded sensors, has been playing an important role in many …

Sensor-based Human Activity Recognition (HAR) is crucial in ubiquitous computing,
analysing behaviours through multi-dimensional observations. Despite research progress …

In recent years, neural network-based soft sensor technology has been widely used in
industrial production processes and has excellent optimization, monitoring, and quality …

The existing deep learning-based methods have shown great potential for the aurora image
classification problem. However, there are many differences in the morphology and …

Abstract Human Activity Recognition (HAR) based on Channel State Information (CSI) has
important application prospects in various fields such as human–computer interactivity …

Continual learning aims to create artificial neural networks capable of accumulating
knowledge and skills through incremental training on a sequence of tasks. The main …