Despite rapid advances, the study highlights significant geographical and thematic imbalances in current research. Nearly half of the reviewed studies were conducted in China, while other critical ...

Abstract: In the context of indoor dense discrete environments, the rapid replanning of paths upon encountering novel obstacles has remained a formidable challenge. Traditional rule-based global path ...

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...

Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a cornerstone of non-invasive brain function investigation, yet its ...

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...