The availability of digital technology in the hands of every citizenry worldwide makes an
available unprecedented massive amount of data. The capability to process these gigantic …

With the rapid development of machine learning, its powerful function in the machine vision
field is increasingly reflected. The combination of machine vision and robotics to achieve the …

In order to ensure the safety measures, the detection of traffic rule violators is a highly
desirable but challenging task due to various difficulties such as occlusion, illumination, poor …

The rapid advancement of technologies has enabled businesses to carryout their activities
seamlessly and revolutionised communications across the globe. There is a significant …

Big data classification is a challenging assignment for the knowledge processing of relevant
information in various domains. Many advanced machine learning (ML) and metaheuristic …

Large volume of multi-structured and low-latency patient data are generated in healthcare
services, which is achallenging task to process and analyze within the Service Level …

With the continuously increasing amount of video data, image set classification has recently
received widespread attention in the CV&PR community. However, the intra-class diversity …

One key challenging problem in data mining and decision-making is to establish a decision
support system based on unbalanced datasets. In this study, we propose a novel algorithm …

Kernel methods have been successfully applied to the areas of pattern recognition and data
mining. In this paper, we mainly discuss the issue of propagating labels in kernel space. A …

Frequency-domain dielectric spectrum (FDS) is an effective testing method to reflect the
changes of internal insulation status of oil-impregnated paper (OIP) bushing. In field …