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OMB Individually Reported

ML-Driven Wide Field Instrument (WFI) Image Calibration

Low riskExact public inventory row

Description

This machine learning-driven project aims to expedite the image calibration process for Roman Wide Field Instrument (WFI) data by developing an automated calibration system. Leveraging advanced AI algorithms, we aim to increase the speed and efficiency of image calibration, particularly for large-scale astronomical surveys and observations.

Detailed example

Trained machine learning models capable of applying flat-field and linearity corrections to WFI images. Automatically calibrated images ready for further analysis. Adaptive calibration parameters tailored to specific observing conditions and instrument characteristics.

AI / analytics pattern

Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.

Automation level / stage

a) Pre-deployment – The use case is in a development or acquisition status.

Expected benefit

Faster calibration processes across all detector outputs Streamlined calibration workflows enable faster processing times, accelerating scientific discoveries.

Controls / human review

ATO: Not reported; PIA: Not published

Source

OMB 2025 Federal Agency AI Use Case Inventory

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