Hel19 Computer Vision Project

TT192021

Updated 2 years ago

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Classes (7)
m1h0
m1h1
m2h0
m2h1
m2h2
m3h2
m3h3

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Description

Here are a few use cases for this project:

  1. Smart Traffic Surveillance: Hel19 can be used to identify and monitor helmet compliance among motorcyclists in real-time. This would help enforce safety regulations, track violations, and potentially lower accident rates caused by helmet non-compliance.

  2. Augmented Reality: Hel19 can be integrated into AR systems to enhance safety instructions in real-time for various users, such as construction workers, bikers, or sports enthusiasts. By recognizing helmets' classes, the system can provide instant guidance on the appropriate type and safety measures relevant to the users' activities.

  3. E-commerce and Retail: Hel19 can help online retailers automatically categorize products in their inventory, making it easier for customers to find the right helmet for their specific needs. Additionally, it can be used in physical stores to track inventory and monitor in-store product displays.

  4. Accident Analysis and Reconstruction: Hel19 can aid in the analysis and reconstruction of accidents involving helmets by correctly identifying helmet types involved in the incidents. This could help insurance companies, law enforcement, and researchers evaluate the effectiveness of different helmet classes in mitigating injuries and improving safety policies.

  5. Helmet Manufacturing Quality Control: Hel19 can be used as a tool for automated quality control in the manufacturing process of helmets. By accurately identifying helmet classes and their specific features, the model can help manufacturers ensure that their products meet required safety standards and specifications.

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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{
                            hel19_dataset,
                            title = { Hel19 Dataset },
                            type = { Open Source Dataset },
                            author = { TT192021 },
                            howpublished = { \url{ https://universe.roboflow.com/tt192021/hel19 } },
                            url = { https://universe.roboflow.com/tt192021/hel19 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-12-22 },
                            }
                        
                    

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