Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …

Objective The aim of this literature review is to yield a comprehensive and exhaustive
overview of the existing evidence and up-to-date applications of artificial intelligence for …

Abstract Southeast Asia, with Indonesia at its core, was the epicentre of the most
extraordinary expansion of global trade ever witnessed along the Maritime Silk Route. But …

Deep Learning (DL) can diagnose faults and assess machine health from raw condition
monitoring data without manually designed statistical features. However, practical …

In the field of brain–computer interfaces (BCIs), the potential for leveraging deep learning
techniques for representing electroencephalogram (EEG) signals has gained substantial …

Self-supervised learning (SSL) is a powerful technique for learning from unlabeled data. By
learning to remain invariant to applied data augmentations, methods such as SimCLR and …

Subsequences with varied regimes in the industrial multivariate time series (MTS) are
closely associated with the dynamic status of the multi-phased industrial process. Time …

Self-supervised learning (SSL) aims to extract useful representations from unlabeled data by
maximizing the agreement between positive pairs. However, traditional SSL relies on …

Analyzing large-scale datasets, especially involving complex and high-dimensional data like
images, is particularly challenging. While self-supervised learning (SSL) has proven …

Pose estimation methods and motion capture systems have opened doors to quan-titative
measurements of animal kinematics. However, these methods are not perfect and contain …