Object Detection(yoloV8) Computer Vision Project
Updated a year ago
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downloadsHere are a few use cases for this project:
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Traffic Management: The model could be used in traffic management systems to detect live objects and classify them for improved traffic data analysis. It could help monitor traffic, track vehicles types, and assist in planning and controlling traffic flow.
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Road Anomaly Detection: The model could provide valuable insights related to road conditions by detecting damages to guide repair and maintenance. This could be instrumental in maintaining road infrastructure.
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Autonomous Driving: Utilizing this model, autonomous vehicles could determine not just other vehicles in their vicinity, but also analyze conditions of the road to adopt best route or avoid potential accidents.
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Safety and Monitoring: This model could also be used in surveillance systems for safety purposes, assisting in identifying classified objects that could pose threats or disruptions.
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Smart Cities Planning: Urban planners could use the model's data on traffic patterns and road conditions to inform advanced city planning, especially in terms of transport routes and road improvements.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
object-detection-yolov8_dataset,
title = { Object Detection(yoloV8) Dataset },
type = { Open Source Dataset },
author = { Daffodil International University },
howpublished = { \url{ https://universe.roboflow.com/daffodil-international-university-kbooi/object-detection-yolov8 } },
url = { https://universe.roboflow.com/daffodil-international-university-kbooi/object-detection-yolov8 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-11-21 },
}