collision detection Object Detection Dataset and Pre-Trained Model by beni suef university

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Explore Dataset

Here are a few use cases for this project:

Space Debris Tracking: The "collision detection" model can be utilized to track and predict potential collision courses of space debris with operational satellites. This can assist spacecraft operators to take preventative measures to avert destruction.
Advance Warning Systems: The model can be implemented in an advanced warning system that alerts scientists and engineers when two space objects, such as satellites or parts of the International Space Station, are on a potential collision path.
Astronomy Research: The model could be used to understand the movement and behavior of celestial bodies, helping researchers and astronomers uncover new knowledge about our universe.
Space Photography and Exploration: The model can be used in space rovers or drones to automatically detect and avoid obstacles while capturing images or exploring extraterrestrial bodies like the moon or other planets.
Satellite Maintenance and Repair: The model could also aid in proactive planning for satellite maintenance, detecting possible problems via an analysis of nearby objects and potential collisions, thus offering a chance to make repairs or adjustments before any damage occurs.

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{ collision-detection_dataset,
    title = { collision detection Dataset },
    type = { Open Source Dataset },
    author = { beni suef university },
    howpublished = { \url{ https://universe.roboflow.com/beni-suef-university-casvi/collision-detection } },
    url = { https://universe.roboflow.com/beni-suef-university-casvi/collision-detection },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { may },
    note = { visited on 2023-12-04 },
}