2020ApJS..248...20H


Query : 2020ApJS..248...20H

2020ApJS..248...20H - Astrophys. J., Suppl. Ser., 248, 20-20 (2020/May-0)

Morpheus: a deep learning framework for the pixel-level analysis of astronomical image data.

HAUSEN R. and ROBERTSON B.E.

Abstract (from CDS):

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.

Abstract Copyright: © 2020. The American Astronomical Society. All rights reserved.

Journal keyword(s): Galaxy classification systems - Galaxies - Extragalactic astronomy - Convolutional neural networks - Computational methods - GPU computing

Simbad objects: 4

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Number of rows : 4
N Identifier Otype ICRS (J2000)
RA
ICRS (J2000)
DEC
Mag U Mag B Mag V Mag R Mag I Sp type #ref
1850 - 2026
#notes
1 NAME GOODS Southern Field reg 03 32 28.0 -27 48 30           ~ 1623 1
2 NAME COSMOS Field reg 10 00 28.60 +02 12 21.0           ~ 3639 0
3 NAME GOODS-N Field reg 12 36 55.0 +62 14 15           ~ 1364 1
4 NAME Extended Groth Strip reg 14 19 +52.8           ~ 1023 0

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