vehical-detection Computer Vision Project

ravi

Updated 3 years ago

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Description

Here are a few use cases for this project:

  1. Traffic Management: This model can be used by city traffic management systems to optimize traffic control settings such as red-light durations, based on vehicle types and density.

  2. Parking Monitoring: The model can aid in the effective management of parking spaces in shopping malls, airports, or city centers, identifying available slots based on the observed vehicles' sizes.

  3. Surveillance Systems: The integration of this model into CCTV networks can help security systems or law enforcement identify specific vehicles in real-time, potentially assisting in cases of stolen vehicles or hit-and-run incidents.

  4. Autonomous Vehicles: Self-driving cars can use this model to identify and navigate around other vehicles on the road, improving their decision-making process and promoting safer transportation.

  5. Analysis of Public Transport Performance: Transportation authorities can apply this model to analyze the frequency and regularity of bus services by counting the number of buses passing a specific point.

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Cite This Project

LICENSE
MIT

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

                        @misc{
                            vehical-detection_dataset,
                            title = { vehical-detection Dataset },
                            type = { Open Source Dataset },
                            author = { ravi },
                            howpublished = { \url{ https://universe.roboflow.com/ravi-twhkr/vehical-detection } },
                            url = { https://universe.roboflow.com/ravi-twhkr/vehical-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jun },
                            note = { visited on 2025-01-18 },
                            }
                        
                    

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