KANNAN-OVERFLOW Computer Vision Project
Here are a few use cases for this project:
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Smart Traffic Monitoring: The KANNAN-OVERFLOW model can be used for monitoring traffic flow within a city, helping authorities identify peak times, frequent vehicle types, and potential problem areas.
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Autonomous Vehicles: It can be incorporated in self-driving car systems to help distinguish between different kinds of vehicles and pedestrians, enhancing safety and driving efficiency.
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Surveillance and Security: It can be used in video surveillance systems to detect and track different classes of vehicles and individuals, contributing to enhanced security in public or private spaces.
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Parking Management: The model can assist in smart parking systems, identifying incoming and outgoing vehicles or bikes, helping to control and plan the parking spaces optimally.
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Transportation Studies: Researchers and urban planners can use the model to carry out comprehensive transportation studies, understanding the mix of vehicle types, pedestrian movement, and devising policies accordingly.
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{
kannan-overflow_dataset,
title = { KANNAN-OVERFLOW Dataset },
type = { Open Source Dataset },
author = { KANNAN },
howpublished = { \url{ https://universe.roboflow.com/kannan-vdngt/kannan-overflow } },
url = { https://universe.roboflow.com/kannan-vdngt/kannan-overflow },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-04-29 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the KANNAN-OVERFLOW project in your project.
