BuildingDetectionWithYoloV8 Computer Vision Project

YoloV3

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Description

Here are a few use cases for this project:

  1. Urban Planning and Development: This model can be used by city planners, architects, and engineers to analyze existing building structures and patterns in urban areas, helping them design and implement better infrastructure and public spaces.

  2. Emergency Response and Disaster Management: The model can provide valuable information to emergency response teams by quickly identifying buildings in affected areas during natural disasters such as earthquakes, hurricanes, and floods, allowing them to prioritize rescue efforts and allocate resources more efficiently.

  3. Environmental Impact Assessment: BuildingDetectionWithYoloV8 can be utilized to evaluate potential environmental impacts of urbanization on surrounding ecosystems by analyzing the density of buildings in specific regions, helping conservationists and policymakers make informed decisions to protect natural habitats.

  4. Real Estate and Property Analysis: The real estate industry can leverage this computer vision model to assess the market value of properties, identifying buildings in desirable locations, and estimating their value based on surrounding infrastructure such as roads, parks, and other amenities.

  5. 3D Mapping and Virtual Reality: This model can be integrated into 3D mapping and VR applications, automatically identifying building structures in satellite or aerial images and converting them into accurate 3D buildings, enhancing the user experience and visual representation of virtual environments.

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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{
                            buildingdetectionwithyolov8_dataset,
                            title = { BuildingDetectionWithYoloV8 Dataset },
                            type = { Open Source Dataset },
                            author = { YoloV3 },
                            howpublished = { \url{ https://universe.roboflow.com/yolov3-tmmts/buildingdetectionwithyolov8 } },
                            url = { https://universe.roboflow.com/yolov3-tmmts/buildingdetectionwithyolov8 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-11-24 },
                            }
                        
                    

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