shujujizhu

pianzhenjiance-colar

Object Detection

pianzhenjiance-colar Computer Vision Project

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Here are a few use cases for this project:

  1. Autonomous Vehicle Navigation: This model can be used in the development of autonomous or semi-autonomous vehicles. The ability to identify different road-pianzhen classes such as cars, trucks, EV drivers and traffic symbols, can contribute to more accurate path-planning and decision-making processes, enhancing vehicle safety and efficiency.

  2. Traffic Management Systems: City authorities or traffic control systems can use this model to monitor and manage traffic congestion in real-time. The algorithm can provide a comprehensive view of vehicles, traffic lights, and pedestrians on roads, aiding in efficient traffic flow management.

  3. Driver Assistance Systems: Manufacturers of cars and electric tricycles can integrate this model into their driver assistance systems. The technology could alert drivers about upcoming cars, pedestrians, traffic lights, and warning signs, thereby increasing safety on roads.

  4. Surveillance and Security: This model can be used in surveillance systems to monitor road activities. Detection of unusual activity, such as non-electric tricycles in areas where only electric tricycles are allowed, or identifying traffic violations can enhance security and rule adherence.

  5. Traffic Study and Urban Planning: Urban planners and researchers can utilize this model to study the behavior of drivers, traffic light efficiency, and pedestrian safety. This can lead to enhanced road designs and policy-making that improves road safety and efficiency.

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{
                            pianzhenjiance-colar_dataset,
                            title = { pianzhenjiance-colar Dataset },
                            type = { Open Source Dataset },
                            author = { shujujizhu },
                            howpublished = { \url{ https://universe.roboflow.com/shujujizhu/pianzhenjiance-colar } },
                            url = { https://universe.roboflow.com/shujujizhu/pianzhenjiance-colar },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-02-29 },
                            }
                        

Connect Your Model With Program Logic

Find utilities and guides to help you start using the pianzhenjiance-colar project in your project.

Source

shujujizhu

Last Updated

10 months ago

Project Type

Object Detection

Subject

Road-pianzhen

Classes

EV driver Electric tricycle Non-C electric tricycle Traffic warning signs car pedestrian traffic light truck

Views: 174

Views in previous 30 days: 0

Downloads: 27

Downloads in previous 30 days: 0

License

CC BY 4.0