Publication

Abstract :

Computer vision is a critical component of artificial intelligence that allows computers to analyze and comprehend visual data. Its applications are numerous, ranging from autonomous vehicles and robotics to surveillance, medical imaging, and augmented reality. Addressing the problem of delayed and inefficient rescue efforts following road accidents is of utmost importance and requires immediate attention. In order to improve accident detection, a proposed method called FRFYOLO combines the random forest algorithm with the YOLOv3 framework. This approach aims to achieve accurate detection of accident events by leveraging the strengths of both algorithms. Experiment results have shown impressive accuracy, with an overall rate of 96%. Implementing this approach has the potential to enhance public safety and emergency response systems across various domains.