fullModel Computer Vision Project
Here are a few use cases for this project:
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Drowsy Driving Detection: The model can be used in a safety system for vehicles, which continually monitors the driver to identify signs of drowsiness or distraction like using a mobile phone. This would help in preventing accidents due to drowsy or distracted driving.
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Child Monitoring System: This model could be integrated into smart home systems to monitor children's activity and alert parents when the child is awake or engaging in potentially risky behaviors like playing with a mobile phone.
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Pedestrian Safety: The model can be utilized in autonomous vehicles or advanced driver assistance systems (ADAS) to detect pedestrians and their state (i.e., whether they are distracted due to mobile usage or interacting with someone), permitting the car to slow down or halt to avoid accidents.
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Human-Robot Interaction: Robots can use this model to better understand humans in their surroundings, particularly in determining whether a person is drowsy, distracted, or managing a child. This could help robots respond more intuitively and assist more efficiently in a variety of circumstances.
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Public Transportation Systems: In bus or train systems, the model could be used to monitor passengers for suspicious behavior, to ensure child safety, or identify distressed or drowsy individuals who may need assistance.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
fullmodel-xwkuv_dataset,
title = { fullModel Dataset },
type = { Open Source Dataset },
author = { Staps },
howpublished = { \url{ https://universe.roboflow.com/staps/fullmodel-xwkuv } },
url = { https://universe.roboflow.com/staps/fullmodel-xwkuv },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { apr },
note = { visited on 2024-04-25 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the fullModel project in your project.
