satellite1 Object Detection Dataset and Pre-Trained Model by satellite1

Images

5005 images

Explore Dataset

Here are a few use cases for this project:

Urban Traffic Monitoring and Management: Satellite1 can be used to analyze satellite images of cities and estimate the number and types of vehicles on roads, providing valuable information to optimize traffic signal timing, identify traffic congestion, and suggest alternate routes for drivers.
Parking Space Management: The model can efficiently detect the types and quantity of vehicles in parking lots, helping in optimizing the allocation of spaces, estimating parking capacity requirements, and providing real-time information for drivers seeking parking spots.
Military and Border Surveillance: Satellite1 can be utilized to detect the presence of military vehicles, such as tanks and armored vehicles, along borders, aiding security forces in assessing security risks and responding to potential threats and incursions in a timely manner.
Disaster Response and Damage Assessment: In the aftermath of natural disasters or accidents, Satellite1 can quickly evaluate satellite imagery to detect blocked roads, stranded or damaged vehicles, and other obstacles that might impede relief efforts or require rapid assistance.
Infrastructure and Transportation Planning: By identifying the types and densities of vehicles in satellite images, urban planners and transportation authorities can gain insights into traffic patterns, usage of existing transportation infrastructure, and the potential need for additional infrastructure or public transit options.

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{ satellite1-k5tpn_dataset,
    title = { satellite1 Dataset },
    type = { Open Source Dataset },
    author = { satellite1 },
    howpublished = { \url{ https://universe.roboflow.com/satellite1/satellite1-k5tpn } },
    url = { https://universe.roboflow.com/satellite1/satellite1-k5tpn },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { feb },
    note = { visited on 2023-11-28 },
}