koraydns/Stellar-Anomaly-Detector
Anomaly Detection in James Webb Space Telescope (JWST) Data using Machine Learning, focusing on identifying maliciously manipulated or falsified data to ensure reliable analysis.
This tool helps astronomers and astrophysicists ensure the integrity of James Webb Space Telescope (JWST) data by identifying maliciously altered or falsified records. You input JWST data—such as timeseries, images, or spectra—and it outputs a list of data points that are likely anomalies. This is ideal for researchers and data analysts working with JWST observations who need to trust their datasets.
Use this if you need to quickly check your JWST datasets for potentially manipulated or falsified entries before proceeding with scientific analysis.
Not ideal if you are looking to detect natural astrophysical anomalies (e.g., supernovae, gravitational lensing) rather than malicious data tampering.
Stars
8
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 28, 2025
Commits (30d)
0
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