dbnnnasa

DBNN.NASA is a project to classify asteroids using a deep neural network trained on 6000 known asteroids with lightcurve data from the NASA WISE project. Our program scrapes the minor planet center’s website for notices of newly discovered asteroids, cross references them with the WISE source database, and classifies them with the neural network. In future, we plan to extend this project by training deep neural networks on WISE image data for simultaneous asteroid detection and classification.

This project is solving the Neuromorphic Studies of Asteroid Imagery challenge.

Description

DBNN.NASA is a project to classify asteroids based on light curves using neural networks. The DL4J library was used to train a deep neural network based on 6000 known asteroids with lightcurve data from the NASA WISE project.

Our program can automatically scrape the minor planet center’s website for notices of newly discovered asteroids, cross reference them with information from the WISE source database to extract light curve data and classify them with the neural network. The GUI consists of a table of the latest 50 asteroids, a map of the locations of the asteroids in earth-centric coordinates, and a visualization of the neural network in action. Users have the option to pull in fresh data off of the internet, or load asteroid references from a file.

In future, we would like to extend this project by running deep neural networks on WISE image data, as well as light curves, for automatic asteroid detection and classification.


Project Information


License: Apache License 2.0 (Apache-2.0)


Source Code/Project URL: https://github.com/j3doucet/DBNN.NASA


Resources


Video - https://www.youtube.com/watch?v=_5a-Q4eLso4

Team

  • Catherine Holloway
  • John Doucette


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