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ExoLumin_ML_MODEL

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Summary

ExoLumin is an AI-driven platform designed to identify potential exoplanets from NASA’s Kepler mission data. The project leverages machine learning models—such as Random Forest and Neural Networks—to analyze key astrophysical parameters (e.g., orbital period, transit depth, planet radius) and classify celestial objects as confirmed planets or false positives. The frontend provides an intuitive interface for researchers to upload candidate data, trigger model predictions, and visualize results interactively. This project addresses the challenge of handling massive astronomical datasets and the limitations of manual classification, enabling faster and more accurate detection of exoplanets. By automating data analysis and offering a clear visualization layer, ExoLumin empowers scientists and enthusiasts to explore distant worlds efficiently, contributing to humanity’s broader understanding of planetary systems beyond our solar system.

Project

https://exolumin-frontend.vercel.app/

Contributors

  • Mahek Bhatia
  • Hirdesh

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