ซ้อนสาม Computer Vision Project
Updated a year ago
Metrics
Here are a few use cases for this project:
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Traffic Monitoring: This model can be used to analyze real-time traffic scenarios, identifying the number of riders on vehicles to provide valuable data for understanding overall traffic patterns, congestion, and the effectiveness of local traffic rules.
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Road Safety Analysis: By recognizing different rider classes, this model can assist in the identification of unsafe behaviors (like overloading of motorcycles) on public roads. This could help to enforce safety regulations and decrease accidents.
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Insurance Companies: Insurance companies could employ this technology to help identify risky behaviors and instances that may breach conditions of insurance policies.
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Law Enforcement: Police could utilize this model to automate the detection of the contravention of traffic rules, such as identifying vehicles carrying more passengers than legally permitted. This could lead to more effective traffic law enforcement.
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Urban Planning: City planners and transportation departments can use the aggregated data from this model to improve road design and identify potential areas of concern due to high congestion or frequent traffic rule breaches.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
-sul9n_dataset,
title = { ซ้อนสาม Dataset },
type = { Open Source Dataset },
author = { l },
howpublished = { \url{ https://universe.roboflow.com/l-fsidg/-sul9n } },
url = { https://universe.roboflow.com/l-fsidg/-sul9n },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-11-24 },
}