mask Computer Vision Project

Alfian Imran

Updated 2 years ago

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Classes (2)
Melanggar
Tidak Melanggar
Description

Here are a few use cases for this project:

  1. Traffic Monitoring and Fines Enforcement: The "mask" model can be employed by traffic authorities to monitor traffic in real-time, identify cars violating traffic rules (Melanggar), and automatically issue fines or warnings to their owners based on the car classes.

  2. Intelligent Traffic Light System: The model can be used in conjunction with traffic lights for adapting green and red times based on Tidak Melanggar (not violating) and Melanggar (violating) car classes. This will improve traffic management systems, aiming to reduce congestion and prioritize the flow of rule-abiding vehicles.

  3. Parking Assistance and Management: "mask" can help in identifying and classifying Tidak Melanggar and Melanggar vehicles entering and exiting parking areas. Parking spaces can be automatically allocated or denied, optimizing parking availability and preventing violator vehicles from occupying spaces.

  4. Road Safety Research: Researchers and transportation authorities can use insights from the "mask" model to study traffic patterns, identify common violations, and propose modifications to road layouts or traffic policies for a safer and more efficient road system.

  5. Insurance Risk Assessment: Insurance companies can utilize the "mask" model to analyze the driving behavior of their policyholders based on the car classes. Vehicles with a higher number of Melanggar instances may be considered riskier, which may lead to higher insurance premiums, while Tidak Melanggar vehicles can be rewarded with better insurance terms.

Supervision

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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{
                            mask-c0fan_dataset,
                            title = { mask Dataset },
                            type = { Open Source Dataset },
                            author = { Alfian Imran },
                            howpublished = { \url{ https://universe.roboflow.com/alfian-imran-x6azu/mask-c0fan } },
                            url = { https://universe.roboflow.com/alfian-imran-x6azu/mask-c0fan },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jan },
                            note = { visited on 2024-12-19 },
                            }
                        
                    

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