@article{713f39a30e2f4cf4b027c270e20ffcd8,
title = "Deep learning for morphological identification of extended radio galaxies using weak labels",
abstract = "The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels of radio galaxies to get class activation maps (CAMs). The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, specifically the Evolutionary Map of the Universe (EMU) Pilot Survey, which covered a sky area of 270 square degrees with an RMS sensitivity of 25-35 Jy beam. We demonstrate that weakly-supervised deep learning algorithms can achieve high accuracy in predicting pixel-level information, including masks for the extended radio emission encapsulating all galaxy components and the positions of the infrared host galaxies. We evaluate the performance of our method using mean Average Precision (mAP) across multiple classes at a standard intersection over union (IoU) threshold of 0.5. We show that the model achieves a mAP of 67.5% and 76.8% for radio masks and infrared host positions, respectively. The network architecture can be found at the following link: https://github.com/Nikhel1/Gal-CAM",
keywords = "Galaxies: active, galaxies: peculiar, Galaxy: evolution, methods: data analysis, radio continuum: galaxies",
author = "Nikhel Gupta and Zeeshan Hayder and Norris, {Ray P.} and Minh Huynh and Lars Petersson and Wang, {X. Rosalind} and Heinz Andernach and Koribalski, {B{\"a}rbel S.} and Miranda Yew and Crawford, {Evan J.}",
note = "Funding Information: The Australian SKA Pathfinder is part of the Australia Telescope National Facility, which is managed by CSIRO. The operation of ASKAP is funded by the Australian Government with support from the National Collaborative Research Infrastructure Strategy. ASKAP uses the resources of the Pawsey Supercomputing Centre. The establishment of ASKAP, the Murchison Radio-astronomy Observatory and the Pawsey Supercomputing Centre are initiatives of the Australian Government, with support from the Government of Western Australia and the Science and Industry Endowment Fund. We acknowledge the Wajarri Yamatji people as the traditional owners of the Observatory site. The photometric redshifts for the Legacy Surveys (PRLS) catalogue used in this paper were produced thanks to funding from the U.S. Department of Energy Office of Science and Office of High Energy Physics via grant DE-SC0007914. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. NG acknowledges support from CSIRO{\textquoteright}s Machine Learning and Artificial Intelligence Future Science (MLAI FSP) Platform. HA has benefited from grant CIIC 138/2022 of Universidad de Guanajuato, Mexico. Publisher Copyright: {\textcopyright} The Author(s), 2023. Published by Cambridge University Press on behalf of the Astronomical Society of Australia.",
year = "2023",
month = sep,
day = "7",
doi = "10.1017/pasa.2023.46",
language = "English",
volume = "40",
journal = "Publications of the Astronomical Society of Australia",
issn = "1323-3580",
publisher = "Cambridge University Press",
}