traffic-accident-yolo8 Computer Vision Project

University Gunadarma

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Description

Here are a few use cases for this project:

  1. Traffic Management Systems: This model could be integrated into traffic monitoring systems to identify and respond to accidents promptly. A real-time alerting mechanism could inform traffic authorities about the exact location and nature of the accident, facilitating quick response and potential saving of life and property.

  2. Autonomous Vehicles: Autonomous vehicles can use this model to assess roads for possible accidents and alter their route or driving behavior to avoid contributing to congestion or causing further accidents.

  3. Insurance Claims Processing: Insurance companies can use this model to classify and assess the damages shown in accident images, aiding in the verification and processing of auto insurance claims.

  4. Road Safety Research: Researchers studying traffic patterns and road safety could use this model to automatically identify accidents in large amounts of image data, simplifying their data analysis and improving their understanding of the causes of accidents.

  5. Traffic News Reporting: Media outlets that report on traffic conditions could use this model to automatically identify and classify traffic accidents from images or live feed, providing more accurate and timely traffic reports to viewers.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            traffic-accident-yolo8_dataset,
                            title = { traffic-accident-yolo8 Dataset },
                            type = { Open Source Dataset },
                            author = { University Gunadarma },
                            howpublished = { \url{ https://universe.roboflow.com/university-gunadarma/traffic-accident-yolo8 } },
                            url = { https://universe.roboflow.com/university-gunadarma/traffic-accident-yolo8 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-10-07 },
                            }