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 GOODS South field, and demonstrate a high completeness in recovering known 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.
- Pub Date:
- June 2019
- Astrophysics - Astrophysics of Galaxies;
- Computer Science - Machine Learning
- 38 pages, 27 figures. Submitted to AAS Journals. More information about Morpheus is available at https://morpheus-project.github.io/morpheus/