london-cranes Object Detection Dataset and Pre-Trained Model by Snail Space

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Explore Dataset

Here are a few use cases for this project:

Construction Safety: Partnering with construction companies to monitor construction sites in London. By identifying different types of cranes on-site, site managers can quickly address potential safety issues or operational inefficiencies.
Urban Planning: Used by city planners and developers in London to analyze the distribution and types of cranes across the city, helping them plan new construction projects.
Real Estate Market Analysis: Helps real estate investors and companies identify areas of high construction activity. A high number of certain crane types might indicate large-scale developments and potential investment opportunities.
Academic Research: Assists researchers in urban studies or civil engineering departments to gather data about construction methods and trends across London.
News Media and Journalism: Assists journalists in investigating and reporting on development trends or construct-related incidents. For instance, journalists could use "london-cranes" to find areas of stress on the city's infrastructure.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            london-cranes_dataset,
                            title = { london-cranes Dataset },
                            type = { Open Source Dataset },
                            author = { Snail Space },
                            howpublished = { \url{ https://universe.roboflow.com/snail-space/london-cranes } },
                            url = { https://universe.roboflow.com/snail-space/london-cranes },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-27 },
                            }