lanedetector Computer Vision Project
Updated 2 years ago
Metrics
Here are a few use cases for this project:
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Autonomous Vehicle Navigation: The "lanedetector" model can be used in self-driving cars to identify and navigate between different lanes, including those marked with LaneLine, thereby ensuring safe travel.
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Traffic Management Systems: Infrastructure and transport authorities can use the model to analyze traffic flow, locate potential traffic hazards or congestion steadily increasing in certain lanes to implement better traffic management solutions.
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Road Maintenance: Government agencies in charge of road maintenance can use the "lanedetector" model to identify lanes or LaneLine that are fading or damaged, prioritizing road repairs and maintenance.
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Traffic Rule Enforcement: The model can be integrated within traffic cameras to identify vehicles that are not adhering to their correct lanes, aiding enforcement of traffic rules.
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Advanced Driver-Assistance Systems (ADAS): The model can be utilized in designing advanced driver-assistance systems by providing real-time lane identification data, aiding in features like lane departure warning and assistance.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
lanedetector-zsct6_dataset,
title = { lanedetector Dataset },
type = { Open Source Dataset },
author = { RDL },
howpublished = { \url{ https://universe.roboflow.com/rdl/lanedetector-zsct6 } },
url = { https://universe.roboflow.com/rdl/lanedetector-zsct6 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2024-12-03 },
}