Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Human activity recognition has been actively studied in the last three decades. Compared to
human action performed by a single person, human interaction is more complex due to the …

Convolutional neural network (CNN), with the ability of feature learning and nonlinear
mapping, has demonstrated its effectiveness in prognostics and health management (PHM) …

This paper presents an intelligent human PC intuitive framework. In this proposed work,
artificial intelligence is utilized for home mechanization, which perceives human motions …

This survey presents a review of state-of-the-art deep neural network architectures,
algorithms, and systems in speech and vision applications. Recent advances in deep …

Many RGB-D visual attention models have been proposed with diverse fusion models; thus,
the main challenge lies in the differences in the results between the different models. To …

Agricultural greenhouses (AGs) are an important facility for the development of modern
agriculture. Accurately and effectively detecting AGs is a necessity for the strategic planning …

Automatic defect recognition is one of the research hotspots in steel production, but most of
the current methods focus on supervised learning, which relies on large-scale labeled …

Automated recognition of human activities or actions has great significance as it
incorporates wide-ranging applications, including surveillance, robotics, and personal …

Abstract Human-Robot Collaboration (HRC), which enables a workspace where human and
robot can dynamically and safely collaborate for improved operational efficiency, has been …