vest_detection_v1 Computer Vision Project
Updated 2 years ago
Metrics
Here are a few use cases for this project:
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Construction Site Safety: The "vest_detection" model can be used to monitor and ensure that workers on construction sites are wearing safety vests, improving compliance and reducing the risk of accidents or injuries.
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Industrial Compliance: In various industrial settings such as factories, warehouses, or logistic centers, employing the "vest_detection" model can help maintain and enforce safety regulations by identifying and alerting management when employees or visitors are not wearing the appropriate safety vests.
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Traffic Police & Emergency Services Uniform Detection: The model can streamline the process of detecting traffic police, paramedics, and other emergency personnel wearing reflective vests in busy or low-visibility environments, allowing quicker assistance, better situational awareness, and improved response times.
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Retail Loss Prevention: The "vest_detection" model can be implemented to identify store employees, security personnel, or maintenance staff wearing vests, enabling efficient tracking of staff movement and aiding in loss prevention efforts by distinguishing between workers and potential shoplifters.
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Outdoor Event Management: The model can be used at outdoor events such as concerts, festivals, or sports games to detect security, medical or volunteer staff wearing identifying vests, allowing organizers to monitor personnel distribution and ensure adequate coverage throughout the event area.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
vest_detection_v1_dataset,
title = { vest_detection_v1 Dataset },
type = { Open Source Dataset },
author = { Mandeep Chauhan },
howpublished = { \url{ https://universe.roboflow.com/mandeep-chauhan-jwvrd/vest_detection_v1 } },
url = { https://universe.roboflow.com/mandeep-chauhan-jwvrd/vest_detection_v1 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { apr },
note = { visited on 2024-11-05 },
}