yolo Object Detection Dataset and Pre-Trained Model by Dronacharya College of Engineering

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Explore Dataset

Here are a few use cases for this project:

Traffic Management Application: The computer vision model could be used in monitoring and managing city traffic. It would be helpful to track vehicles and license plates, especially in identifying vehicles involved in violations such as speeding or running red lights.
Parking Lot Management: The model can be used in automated parking systems to identify and record the number plates of vehicles entering or exiting a parking area. This would help in tracking parking time and calculating parking fees, and also ensure security by keeping record of all vehicles using the space.
Security and Surveillance: For both public and private security purposes, YOLO can be used to monitor vehicles entering a specified area. For instance, in gated communities, commercial complexes, or government buildings, it can provide real-time updates of all vehicles coming in and going out.
Auto Theft Detection: Law enforcement and security agencies can utilize this computer vision model to monitor and identify stolen vehicles. By integrating it with a database of stolen vehicle license plates, it could identify when a stolen vehicle is in a given area.
Toll Collection: This model can be used by highway toll collection systems to automate the process of identifying vehicle number plates, thus speeding up the process and increasing the overall efficiency of toll collection.

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{
                            yolo-unszn_dataset,
                            title = { yolo Dataset },
                            type = { Open Source Dataset },
                            author = { Dronacharya College of Engineering },
                            howpublished = { \url{ https://universe.roboflow.com/dronacharya-college-of-engineering/yolo-unszn } },
                            url = { https://universe.roboflow.com/dronacharya-college-of-engineering/yolo-unszn },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-05-08 },
                            }