This project is a deep learning-based accident detection system that analyzes surveillance video footage to identify road accidents in real-time. The model uses Conv3D and ConvLSTM2D architectures to ...

This project develops an intelligent accident detection system using deep learning and IoT. Leveraging real-time traffic feeds, it combines a classification model to identify accidents, YOLOv5 to ...

We propose an architecture VANET for accident detection using deep learning methods within this context. Consequently, we evaluated the performance of Mask R-CNN, SOLO, YOLOv6 and YOLOv7 deep learning ...

This paper presents a real-time road accident detection and alert system that leverages a custom sequential CNN model optimized for rapid accident identification. Unlike existing approaches, this ...