This research paper examines the potential of artificial intelligence (AI) in strengthening data
security and mitigating the growing threat of cyber-attacks. As digital threats continue to …

Generalization remains a central challenge in machine learning. In this work, we propose
Learning from Teaching (LoT), a novel regularization technique for deep neural networks to …

Self-supervised representation learning methods have achieved significant success in
computer vision and natural language processing (NLP), where data samples exhibit explicit …

This paper presents a novel contribution to the field of regional style transfer. Existing
methods often suffer from the drawback of applying style homogeneously across the entire …

With the rapid growth of global e-commerce, the demand for automation in the logistics
industry is increasing. This study focuses on automated picking systems in warehouses …

Electroencephalography (EEG) signals are crucial for investigating brain function and
cognitive processes. This study aims to address the challenges of efficiently recording and …

Trauma is a significant cause of mortality and diagnostic methods for traumatic injuries, such
as X-rays, CT scans, and MRI, are often time-consuming and dependent on medical …

This paper explores the application and effectiveness of adaptive machine learning systems
in heterogeneous data environments. With the diversification of data sources and types …

This article presents novel designs of autonomous UAV prototypes specifically developed
for inspecting GPS-denied tunnel construction environments with dynamic human and …

In the context of global trade, cross-border commodity pricing largely determines the
competitiveness and market share of businesses. However, existing methodologies often …