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object-detection-vxyo1/1 (latest)
object detection Computer Vision Project
Henujan
Updated 2 years ago
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Classes (5)
Metrics
mAP is equal to the average of the Average Precision metric across
all
classes in a
model.
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mAP
Precision measures how often your model's predictions are correct.
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Precision
Recall measures what percentage of relevant labels were successfully
identified.
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Recall
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Description
Here are a few use cases for this project:
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Traffic Monitoring: The object detection model can be used in traffic control systems to automate the process of identifying motorbike riders, differentiating bikers with helmets from those without, thereby encouraging safety regulations.
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Law Enforcement: They can be used by traffic police to swiftly identify traffic rule violators such as motorbike riders without a helmet or to detect and track specific number plates.
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Accident Analysis: In case of road accidents, investigators can use this model to analyze CCTV footage to determine whether the motorbike riders were wearing helmets at the time of an accident.
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Advanced Driver-Assistance Systems (ADAS): Companies developing ADAS or self-driving technologies can use this model to detect and classify motorbikes and relevant sub-classes to ensure safe navigation.
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License Plate Recognition Systems: This model could aid parking authorities or toll booths in identifying the number plates of motorbikes quickly and accurately.
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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{
object-detection-vxyo1_dataset,
title = { object detection Dataset },
type = { Open Source Dataset },
author = { Henujan },
howpublished = { \url{ https://universe.roboflow.com/henujan/object-detection-vxyo1 } },
url = { https://universe.roboflow.com/henujan/object-detection-vxyo1 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { oct },
note = { visited on 2025-03-11 },
}
