{"url":"/dataset/radiogalaxynet-dataset","name":"RadioGalaxyNET Dataset","full_name":null,"description_markdown":"Automating the creation of catalogues for radio galaxies in next-generation deep surveys necessitates the identification of components within extended sources and their respective infrared hosts. We present RadioGalaxyNET, a multimodal dataset, tailored for machine learning tasks to streamline the automated detection and localization of multi-component extended radio galaxies and their associated infrared hosts. The dataset encompasses 4,155 instances of galaxies across 2,800 images, incorporating both radio and infrared channels. Each instance furnishes details about the extended radio galaxy class, a bounding box covering all components, a pixel-level segmentation mask, and the keypoint position of the corresponding infrared host galaxy. RadioGalaxyNET is the first dataset to include images from the highly sensitive Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope, corresponding infrared images, and instance-level annotations for galaxy detection.","description_withheld":null,"homepage":"https://doi.org/10.25919/btk3-vx79","introduced_date":"2023-12-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/radiogalaxynet-dataset-and-novel-computer","title":"RadioGalaxyNET: Dataset and Novel Computer Vision Algorithms for the Detection of Extended Radio Galaxies and Infrared Hosts","first_author":"Nikhel Gupta","url":null},"license":{"name":"Creative Commons Attribution Noncommercial-Share Alike 4.0 Licence","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"},{"name":"Keypoint Detection","url":"/task/keypoint-detection","datasets_with_task":"/datasets/task/keypoint-detection"}],"languages":[],"variants":["RadioGalaxyNET Dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/2d-object-detection-on-radiogalaxynet-dataset","task":"2D Object Detection","dataset_variant":"RadioGalaxyNET Dataset","rows":1,"metrics":["COCO-style AP"],"first_row_in_archive_order":{"model":"Gal-DINO","paper":"/paper/radiogalaxynet-dataset-and-novel-computer","metrics":{"COCO-style AP":"Read Paper for Gal-DINO results in Table 2."},"code_links":[{"title":"nikhel1/gal-detr","url":"https://github.com/nikhel1/gal-detr"},{"title":"nikhel1/gal-deformable-detr","url":"https://github.com/nikhel1/gal-deformable-detr"},{"title":"nikhel1/gal-dino","url":"https://github.com/nikhel1/gal-dino"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/radiogalaxynet-dataset-and-novel-computer","title":"RadioGalaxyNET: Dataset and Novel Computer Vision Algorithms for the Detection of Extended Radio Galaxies and Infrared Hosts","date":"2023-12-01","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}