Object Detection

FYP2 Computer Vision Project


2294 images
Explore Dataset

Here are a few use cases for this project:

  1. Accident Insurance Claims: The model can be used by insurance companies to quickly process accident claims. If a client submits a photo of their damaged vehicle, the model could identify the type of vehicle and the extent of the damage, speeding up claim processing.

  2. Traffic Analysis and Control: The model can be integrated into smart cities' digital infrastructure to monitor traffic conditions, identify accidents, and deploy appropriate emergency vehicles (ambulance, fire trucks, or police).

  3. Autonomous Vehicle Systems: The computer vision model could be integrated into the systems of self-driving cars, where it could identify various types of vehicles and incidents, helping the autonomous system make safer decisions on the road.

  4. Emergency Response Planning: The model can be used by emergency services to scan live camera feeds or drone footage during disasters or accidents, quickly identifying the number and type of vehicles involved, and people who may be injured.

  5. Augmented Reality Training for First responders: The model can be employed within AR-based training programs for emergency responders. It can simulate various road accident scenarios, which can help trainees understand how to react in different situations.

Cite this Project

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

@misc{ fyp2-vhjqb_dataset,
    title = { FYP2 Dataset },
    type = { Open Source Dataset },
    author = { FYp },
    howpublished = { \url{ https://universe.roboflow.com/fyp-dsokx/fyp2-vhjqb } },
    url = { https://universe.roboflow.com/fyp-dsokx/fyp2-vhjqb },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2021 },
    month = { nov },
    note = { visited on 2023-12-02 },

Find utilities and guides to help you start using the FYP2 project in your project.



Last Updated

2 years ago

Project Type

Object Detection




Accident, Bike, Boat, Bus, Car, Cycle, Emergency, Fire Emergency, Heli copter, Injured Person, Jeep, Person, Scrap, Tank, Truck, Van

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