{"url":"/dataset/deepspaceyolodataset","name":"DeepSpaceYoloDataset","full_name":null,"description_markdown":"During the MILAN research project (MachIne Learning for AstroNomy), we have compiled a large collection of deep sky images during Electronically Assisted Astronomy sessions in Luxembourg, France, Belgium.\r\n\r\nWe have used two instruments for several months (from March 2022 to September 2023): a Stellina smart telescope (https://vaonis.com/stellina) and a Vespera smart telescope (https://vaonis.com/vespera).\r\nWe have captured data for a representative set of deep sky objects from the Messier / NGC / IC / Sharpless2 / Barnard catalogues.\r\nDifferent types of celestial objects were considered: emission/reflection/dark/planetary nebula, galaxies, globular/open clusters.\r\nImages were obtained after the capture and the stacking of sub-frames of 10 seconds exposure time.\r\nTraining images were splitted into 608x608 patches.\r\nBased on the YOLOv7 format, the dataset is a ZIP file containing 4696 RGB images, and the corresponding 4696 labels text files with the positions of deep sky objets in the images. \r\n\r\nThis research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.\r\n\r\nMore information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.\r\n\r\nMore information about VAONIS instruments: https://vaonis.com\r\n\r\nMore information about Luxembourg of Science and Technology (LIST): https://www.list.lu","description_withheld":null,"homepage":"https://zenodo.org/records/8387071","introduced_date":"2023-11-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/detection-d-objets-celestes-dans-des-images","title":"Détection d'objets célestes dans des images astronomiques par IA explicable","first_author":"Olivier Parisot","url":null},"license":{"name":"Attribution-NonCommercial-NoDerivatives 4.0 International","url":"https://zenodo.org/records/8387071/files/LICENCE.txt"},"modalities":[],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"}],"languages":[],"variants":["DeepSpaceYoloDataset"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}