emergency_vehicles Object Detection Dataset and Pre-Trained Model by emergencyvehicles

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Explore Dataset

Here are a few use cases for this project:

Traffic Management Systems: The "emergency_vehicles" model can be integrated into traffic management systems so they can detect the types of emergency vehicles on the road. This can allow traffic lights to automatically change, giving priority to emergency vehicles, thereby improving response times and saving lives.
Smart Surveillance Systems: This computer vision model can be utilized as part of smart surveillance system infrastructure in cities to indicate the presence and movement of emergency vehicles, which could be crucial information during natural disasters or mass emergencies.
Autonomous Vehicle Navigation: The model can be used in autonomous vehicles to detect different types of emergency vehicles, their speed, and direction. This can help the autonomous vehicle to respond appropriately, ensuring safety.
Fleet Management for Emergency Services: This model can help manage the fleet of emergency vehicles by tracking and identifying which types of vehicles are being used or are idle, ultimately improving efficiency and preparedness.
Emergency Scenario Training Programs: The computer vision model can be used for training purposes in virtual reality or augmented reality applications for first responders and emergency personnel, helping them to learn how to identify different types of emergency vehicles quickly.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            emergency_vehicles-stz1b_dataset,
                            title = { emergency_vehicles Dataset },
                            type = { Open Source Dataset },
                            author = { emergencyvehicles },
                            howpublished = { \url{ https://universe.roboflow.com/emergencyvehicles/emergency_vehicles-stz1b } },
                            url = { https://universe.roboflow.com/emergencyvehicles/emergency_vehicles-stz1b },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-04-29 },
                            }