EGO Computer Vision Project

ABAJA

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Classes (9)
30
60
80
GO
STOP bike car person
person-like
Description

Here are a few use cases for this project:

  1. Smart Traffic Management: The "new_classes" model can be integrated into traffic monitoring systems to automatically identify traffic signs and adjust traffic signals in real-time, optimizing traffic flow and reducing congestion.

  2. Autonomous Vehicles: The model can be implemented in self-driving cars to accurately recognize traffic signs and adjust the vehicle's speed according to the detected speed limits, enhancing safety and compliance with traffic rules.

  3. Road Safety Applications: The "new_classes" model can be used in mobile applications for drivers, alerting them of upcoming traffic signs (such as speed limits or no-waiting zones) to improve road safety and assist in navigation.

  4. Traffic Sign Inventory Management: Authorities can use the model to automatically catalog and maintain the database of traffic signs in their jurisdiction, simplifying the process and helping prioritize maintenance and replacement activities.

  5. Driving Simulation and Training: The "new_classes" model can be employed in driving simulators, providing realistic and accurate traffic-sign recognition to better train future drivers and assess their ability to comply with traffic regulations.

Supervision

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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{
                            ego-tdqtu_dataset,
                            title = { EGO Dataset },
                            type = { Open Source Dataset },
                            author = { ABAJA },
                            howpublished = { \url{ https://universe.roboflow.com/abaja/ego-tdqtu } },
                            url = { https://universe.roboflow.com/abaja/ego-tdqtu },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { sep },
                            note = { visited on 2024-11-22 },
                            }
                        
                    

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