Computer-based accident detection carried out using video surveillance which has become advantageous but a difficult job. Recent framework has been proposed to detect accidents of the vehicles. This framework utilizes YOLO for detection of vehicle accidents with better efficiency and would avoid false ...
The Accident Detection Application provides a graphical user interface (GUI) for detecting accidents using YOLO. It supports both image file detection and live camera feed detection, making it versatile and easy to use. Features ✨ Image File Detection: Detect accidents in image files. Live Came...
This repository contains accident classification and traffic analysis using Yolo-v5 and machine learning in real-time and store data in firebase. machine-learning firebase deep-learning sms-api accident-detection yolov5 Updated May 11, 2021 Jupyter Notebook saswatsamal / anticollider Star 3 Code...
Qiu Q, Lau D (2023) Real-time detection of cracks in tiled sidewalks using YOLO-based method applied to unmanned aerial vehicle (UAV) images. Autom Constr 147:104745 Article MATH Google Scholar Shao Y, Yang Z, Li Z, Li J (2024) Aero-YOLO: an efficient vehicle and pedestrian detection...
On the more complex COCO2017 dataset, the detection accuracy did not drop much compared with the CTS dataset, with the mAP value of 81.50% before the improvement of YOLOv4 and 84.16% after the improvement, an improvement of 2.66%, and 88.53%, an improvement of 2.36%. These experimental ...
YOLOv8 RoboflowSetup GuideFirstly clone this repo locally(if you want you can fork it and clone it too) : git clone https://github.com/ebraj/Accident-Detection-Web-App.git Once cloned successfully, open this project in your favourite IDE(VSCode in my case)Backend...
Step 3: For object detection and classification of approaching vehicles, the processing unit utilizes an artificial intelligence system called YOLOv8. This AI system can identify six types of objects: person, bicycle, car, motorcycle, bus, and truck. ...
YOLOv5s-M: A deep learning network model for road pavement damage detection from urban street-view imagery Int. J. Appl. Earth Obs. Geoinformation, 120 (2023), Article 103335, 10.1016/j.jag.2023.103335 View PDFView articleView in ScopusGoogle Scholar Song et al., 2021 L. Song, W. (Davi...
This paper presents a new efficient framework for accident detection at intersections for traffic surveillance applications. The proposed framework consists of three hierarchical steps, including efficient and accurate object detection based on the state-of-the-art YOLOv4 method, object tracking based on...
This study presents an accident detection system leveraging the YOLOv3 model for real-time identification of head-on collisions, rear-end collisions, and vehicle rollovers. The YOLOv3 model was trained and fine-tuned on a unique dataset of accident photos following pre-training on the COCO ...