The concept of intelligent visual identification of abnormal human activity has raised the
standards of surveillance systems, situation cognizance, homeland safety and smart …

Human action recognition plays a fundamental role in the design of smart solution for home
environments, particularly in relation to ambient assisted living applications, where the …

Availability of handy RGB-D sensors has brought about a surge of gesture recognition
research and applications. Among various approaches, one shot learning approach is …

The aim of Active and Assisted Living is to develop tools to promote the ageing in place of
elderly people, and human activity recognition algorithms can help to monitor aged people …

Artificial autonomous agents and robots interacting in complex environments are required to
continually acquire and fine-tune knowledge over sustained periods of time. The ability to …

Inspired by the success of deep learning methods, for human activity recognition based on
individual vision cues, this paper presents a ConvNets based approach for activity …

Utilizing machine learning methods to detect intrusion into computer networks is a trending
topic in information security research. The limitation of labeled samples is one of the …

Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning
of knowledge through experience. However, conventional deep neural models for action …

With advances in consumer electronics, demands have increased for greater granularity in
differentiating and analyzing human daily activities. Moreover, the potential of machine …

The deep learning techniques have achieved great success in the application of human
activity recognition (HAR). In this paper, we propose a technique for HAR that utilizes the …