connection Object Detection Dataset and Pre-Trained Model by connection

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Explore Dataset

Here are a few use cases for this project:

Public Health Compliance: This model could be implemented in public spaces, such as shopping malls, schools, restaurants, and transportation hubs to measure and analyze the degree of social distancing practiced. It could provide real-time alerts if/when individuals are not following social distancing guidelines, helping to improve public health safety.
Workplace Safety: Companies could use this model to ensure that their employees are following social distancing measures in shared office spaces or manufacturing floors, thus enhancing workplace safety during pandemic situations.
Event Monitoring: This model could be beneficial for event organizers, who can use it to monitor social distancing during large gatherings or outdoor events like concerts, seminars, or sports matches. It could help enforce regulations and assess risk levels.
Urban Planning: Urban planners and developers could use this model to understand how people navigate public spaces, and use the insights to design more effective social distancing solutions in parks, sidewalks, and other public amenities.
Law Enforcement: Authorities could potentially utilize this model to monitor public areas and enforce social distancing guidelines, aiding in pandemic response efforts.

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{ connection_dataset,
    title = { connection Dataset },
    type = { Open Source Dataset },
    author = { connection },
    howpublished = { \url{ https://universe.roboflow.com/connection-acsf6/connection } },
    url = { https://universe.roboflow.com/connection-acsf6/connection },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { may },
    note = { visited on 2023-12-11 },
}