Deep Learning Anomaly Detection
ORAL
Abstract
WFC3/IR data has shown a range of known anomalies that are consistently occurring and have known corrections using pipeline processing. The Quicklook project is a data management software for quick access to and inspection of Hubble Space Telescope Wide Field Camera 3 data. One of the features of the projects is anomaly detection, which allows Quicklook team members to visually inspect new observations and flag them for anomalies. We introduce a method for creating a deep learning algorithm to complement the existing Quicklook software by automatically detecting known and unknown WFC3 image anomalies, thus improving detection accuracy and reducing time spent on manual image inspection.
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Authors
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Afra Ashraf
Barnard College
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Jonathan Fraine
Space Science Institute
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Jennifer Medina
Space Telescope Science Institute
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Heather Olszewski
Space Telescope Science Institute