期刊
ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES
卷 248, 期 1, 页码 -出版社
IOP Publishing Ltd
DOI: 10.3847/1538-4365/ab8868
关键词
Galaxy classification systems; Galaxies; Extragalactic astronomy; Convolutional neural networks; Computational methods; GPU computing
资金
- NASA [NAS5-26555, NNG16PJ25C]
- NSF MRI [AST 1828315]
- Eugene V. Cota-Robles Fellowship
- 3D-HST Treasury Program [GO 12177, 12328]
We present Morpheus, a new model for generating pixel-level morphological classifications of astronomical sources. Morpheus leverages advances in deep learning to perform source detection, source segmentation, and morphological classification pixel-by-pixel via a semantic segmentation algorithm adopted from the field of computer vision. By utilizing morphological information about the flux of real astronomical sources during object detection, Morpheus shows resiliency to false-positive identifications of sources. We evaluate Morpheus by performing source detection, source segmentation, morphological classification on the Hubble Space Telescope data in the five CANDELS fields with a focus on the GOODS South field, and demonstrate a high completeness in recovering known GOODS South 3D-HST sources with H < 26 AB. We release the code publicly, provide online demonstrations, and present an interactive visualization of the Morpheus results in GOODS South.
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