This study analyses the main challenges, trends, technological approaches, and artificial
intelligence methods developed by new researchers and professionals in the field of …

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 …

An enormous amount of clinical free-text information, such as pathology reports, progress
reports, clinical notes and discharge summaries have been collected at hospitals and …

In an electroencephalogram-(EEG-) based brain–computer interface (BCI), a subject can
directly communicate with an electronic device using his EEG signals in a safe and …

Electroencephalogram (EEG) signals are generated from central nervous system which are
difficult to disguise, leading to its popularity in emotion recognition. Recently, semi …

Semi-supervised learning (SSL) methods, which exploit both the labeled and unlabeled
data, have attracted a lot of attention. One of the major categories of SSL methods, graph …

Electroencephalogram (EEG) signals are widely used in the field of emotion recognition
since it is resistant to camouflage and contains abundant physiological information …

Semi-supervised learning (SSL) based on manifold regularization in many fields has
attracted widespread attention and research. However, SSL still has two main challenges …

Semi-supervised self-labeled methods apply unlabeled data to improve the performance of
classifiers which are trained by labeled data alone. Nevertheless, applying unlabeled data …

Many semi-supervised learning methods have been developed in recent years, especially
graph-based approaches, which have achieved satisfactory performance in the practical …