What question did this study set out to answer?

Develop an automated software tool (SExtractor) to reliably detect, deblend, measure, and classify celestial objects in large astronomical datasets.

June 1, 1996Astronomy and Astrophysics Supplement SeriesOpen Access

SExtractor: Software for source extraction

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Authors

EBE. BertinCentre National de la Recherche Scientifique SAS. ArnoutsUniversity of Hawaiʻi at Mānoa

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Implication

Computational study demonstrates automated source extraction and classification in astronomical images, highlighting its utility for large extragalactic surveys.

Key Points

Develop an automated software tool (SExtractor) to reliably detect, deblend, measure, and classify celestial objects in large astronomical datasets.
Engineered automated algorithms to detect, deblend, and measure celestial sources across diverse object shapes and magnitudes with minimal manual intervention.
Trained an artificial neural network on simulated sky images to perform robust automated star/galaxy separation.
Achieved reliable star/galaxy classification across diverse imaging conditions using the trained neural network.
Enabled efficient automated processing of very large imaging datasets containing wide variations in object morphology and brightness.

Cite This Study

Bertin et al. (1996) studied this question.

synapsesocial.com/papers/69d8235da2a48916bbbef43c https://doi.org/10.1051/aas:1996164

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Implication

Computational study demonstrates automated source extraction and classification in astronomical images, highlighting its utility for large extragalactic surveys.

SExtractor: Software for source extraction

Discussion

Member takes

Implication

Key Points

Cite This Study

SExtractor: Software for source extraction

Discussion

Member takes

Implication

Key Points

Cite This Study

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