mh-obj Computer Vision Project

new-workspace-igync

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Description

Here are a few use cases for this project:

  1. Safety Compliance Monitoring: Use "mh-obj" computer vision model for real-time surveillance in workplaces such as construction sites, factories or mines to ensure all employees are wearing appropriate safety gear (helmets or masks) based on the situation.

  2. Healthcare Settings: The model can identify if medical personnel, patients, or visitors are wearing masks in required settings, such as hospitals or clinics, to ensure regulatory compliance and minimize the spread of infectious diseases.

  3. Facial Recognition Systems: Improve the accuracy of facial recognition systems by firstly identifying individuals wearing masks or helmets, hence enabling better detection of partial faces.

  4. Transportation Safety: Use in public transportation networks to make sure riders are following safety guidelines, such as wearing masks on buses or trains during a pandemic, or helmets when riding on motorbikes.

  5. Sports Analytics: Employ the model in the sports industry for automated detection of sports players, whether they are wearing their required safety helmets or not. The model can aid in enforcing safety standards during games and training sessions.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            mh-obj_dataset,
                            title = { mh-obj Dataset },
                            type = { Open Source Dataset },
                            author = { new-workspace-igync },
                            howpublished = { \url{ https://universe.roboflow.com/new-workspace-igync/mh-obj } },
                            url = { https://universe.roboflow.com/new-workspace-igync/mh-obj },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2021 },
                            month = { sep },
                            note = { visited on 2024-11-14 },
                            }
                        
                    

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