In large public places such as railway stations and airports, dense pedestrian detection is
important for safety and security. Deep learning methods provide relatively effective …

Abnormal crowd behavior recognition is one of the research hotspots in computer vision. Its
goal is to use computer vision technology and abnormal behavior detection models to …

Video surveillance is widely adopted across various sectors for purposes such as law
enforcement, COVID-19 isolation monitoring, and analyzing crowds for potential threats like …

Abnormal crowd detection and estimation are critical in video surveillance for ensuring
public safety and preventing stampedes. Owing to occlusions and blind spots, traditional …

Crowd Density Detection in Smart Video Surveillance involves advanced computer vision
(CV) techniques to improve the efficiency and accuracy of crowd monitoring. The system …

The interest in leveraging Artificial Intelligence (AI) for surgical procedures to automate
analysis has witnessed a significant surge in recent years. One of the primary tools for …

Crowd abnormal behavior recognition is one of the research hotspots in computer vision. Its
goal is to use computer vision technology and abnormal behavior detection models to …

Neutrosophic set (NS) and Neutrosophic logic (NL) play a major part in approximation
theory. They are generalizations of intuitionistic fuzzy sets and logic correspondingly. Rough …

Understanding crowd dynamics in densely populated public spaces, such as city centers,
stadiums, and transit hubs, is vital for ensuring public safety and efficient management. The …