During about 30 years, a lot of research teams have worked on the big challenge of
detection of moving objects in various challenging environments. First applications concern …

At present, ML has become an effective method to solve the prediction problem of fatigue
crack growth. To reduce the inaccurate prediction caused by uncertain factors in crack …

Active learning provides guidance for the design and modeling of systems with highly
expensive sampling costs. However, existing active learning approaches suffer from cold …

This paper proposes an approach to predicting fatigue crack growth under mixed-mode
loading based on improved Gaussian process. In terms of analyzing the theoretical …

We investigate spatio-temporal event analysis using point processes. Inferring the dynamics
of event sequences spatio-temporally has many practical applications including crime …

Neonatal seizures are sudden events in brain activity with detrimental effects in neurological
functions usually related to epileptic fits. Though neonatal seizures can be identified from …

Determination of whether or not the electroencephalography (EEG) ambient signal is
Gaussian-distributed is important for a variety of engineering applications, such as cognitive …

A large number of scientific studies involve high-dimensional spatiotemporal data with
complicated relationships. In this paper, we focus on a type of space-time interaction named …

Society 5.0 is based on environmental sensor information, equipment operating status,
people related information, etc. A part of this information comes from video surveillance …

We investigate the problem of predicting the expected lifetime of a material in different
climatic conditions from a few observations in sparsely located testing facilities. We propose …