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 …

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

Private inference (PI) has emerged as a promising solution to execute computations on
encrypted data, safeguarding user privacy and model parameters in edge computing …

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

This survey reviews the phenomenon of rumor propagation in social networks, defining
rumors and their manifestations, and highlighting the societal confusion, panic, and harm …

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

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 …

Lung cancer remains a leading cause of cancerrelated deaths globally, with non-small cell
lung cancer (NSCLC) being the most common subtype. This study aimed to identify key …

Integrating IoT technology into basketball action recognition enhances sports analytics,
providing crucial insights into player performance and game strategy. However, existing …

Real-time lower limb movement resistance monitoring is critical for various applications in
clinical and sports settings, such as rehabilitation and athletic training. Current methods …