image annotation Computer Vision Project
Updated 3 years ago
Here are a few use cases for this project:
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Traffic Monitoring Systems: This model can be deployed in real-time traffic surveillance systems for the identification of different types of vehicles and individuals, allowing for better traffic management and improving road safety.
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Autonomous Vehicles: The image annotation model could be used in self-driving cars to identify surrounding objects such as bikes, cars, and people, enabling autonomous navigation and making on-road decisions.
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Parking Management: The model can help to automate the process of monitoring and managing parking lots by identifying the types of vehicles parked, their count and even anomalous objects.
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Security and Surveillance: If integrated into CCTV systems, the model can detect and classify objects and individuals in the live feed, providing real-time analysis essential for security and surveillance measures.
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Smart City Infrastructure: The model can form part of the foundational technologies for a smart city, aiding in urban planning, transportation regulation, and enhancing the overall efficiency of the city's traffic system.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
image-annotation-qupli_dataset,
title = { image annotation Dataset },
type = { Open Source Dataset },
author = { 28032022 },
howpublished = { \url{ https://universe.roboflow.com/28032022/image-annotation-qupli } },
url = { https://universe.roboflow.com/28032022/image-annotation-qupli },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { apr },
note = { visited on 2024-12-31 },
}