This repository contains the code and supplementary materials for the paper "ExoSpikeNet: A Light Curve Analysis Based Spiking Neural Network for Exoplanet Detection," co-authored by Maneet Chatterjee, Anuvab Sen, and Subhabrata Roy. Our research introduces a novel approach using Spiking Neural Networks (SNNs) for classifying exoplanets from light curve data obtained from the Kepler (K2) mission.
- Spiking Neural Network (SNN) Implementation: An innovative approach for analyzing light curves and detecting exoplanets.
- Comparison with Traditional Models: Performance evaluation against conventional machine learning and deep learning models.
- Data Processing: Tools for handling and processing large datasets, including light curves and associated labels.
- Python 3.x
- Required Python libraries: TensorFlow, NumPy, Pandas, Matplotlib, Scikit-learn, etc.
- [Include any other dependencies or software requirements]
Clone the repository:
git clone https://github.com/maneet2004/Exoplanet-Classification-using-Spiking-Neural-NetworksContributions to this project are welcome. Please open an issue or submit a pull request if you have suggestions or improvements.
This project is licensed under the MIT License.
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