teknofest Object Detection Dataset and Pre-Trained Model by Yamur Akn

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Explore Dataset

Here are a few use cases for this project:

Traffic Monitoring and Analysis: The teknofest computer vision model can be employed in traffic management systems to monitor and analyze different types of vehicles on the road, such as cars, trucks, motorcycles, trams, and buses. It can help optimize traffic signal timings and improve road safety by detecting potentially dangerous situations, such as overcrowded pedestrian areas or obstacles on the road.
Automated Toll Collection: The model can be integrated into electronic toll collection systems to automatically identify and classify vehicles passing through toll booths. This can streamline the toll payment process, reducing wait times and increasing overall efficiency.
Parking Management: The teknofest model can be used in parking lot management systems to determine the occupancy and availability of spaces. By recognizing and classifying the type of vehicles, the system can optimize parking space allocation, ensuring efficient use of available spaces and preventing unauthorized parking.
Surveillance and Security: The model can be implemented in security systems to detect and identify unauthorized vehicles or unusual activities in restricted areas, such as airports, railway stations, or military bases. It can also help monitor pedestrian activity in these areas, enabling fast response to emergency situations or potential threats.
Smart City Applications: The teknofest model can be integrated into various smart city applications, such as intelligent transportation systems, urban planning, and infrastructure maintenance. By providing accurate information about the types of vehicles moving through the city and their interaction with various urban features, the model can help city planners and administrators make well-informed decisions to improve urban environments and overall quality of life.

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{
                            teknofest-tpnj0_dataset,
                            title = { teknofest Dataset },
                            type = { Open Source Dataset },
                            author = { Yamur Akn },
                            howpublished = { \url{ https://universe.roboflow.com/yamur-akn/teknofest-tpnj0 } },
                            url = { https://universe.roboflow.com/yamur-akn/teknofest-tpnj0 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-04-29 },
                            }