Deep neural networks (DNNs) are currently being deployed as machine learning technology
in a wide range of important real-world applications. DNNs consist of a huge number of …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …

The exoskeleton is mainly used by subjects who suffer muscle injury to enhance motor
ability in the daily life environment. Previous research seldom considers extending human …

Graph representation learning has re-emerged as a fascinating research topic due to the
successful application of graph convolutional networks (GCNs) for graphs and inspires …

As the controller parameter adjustment process is simplified significantly by using learning
algorithms, the studies about learning-based control attract a lot of interest in recent years …

Owing to the powerful data representation ability of deep learning (DL) techniques,
tremendous progress has been recently made in hyperspectral image (HSI) classification …

Computer vision (CV) is a big and important field in artificial intelligence covering a wide
range of applications. Image analysis is a major task in CV aiming to extract, analyze and …

We propose an adaptive neural-network-based fault-tolerant control scheme for a flexible
string considering the input constraint, actuator gain fault, and external disturbances. First …

The lane-change decision-making module of automated and connected vehicles (ACVs) is
one of the most crucial and challenging issues to be addressed. Motivated by human beings' …