{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/data-and-models-for-sunspots-detection-in","title":"Data and models for sunspots detection in solar images captured with smart telescopes","arxiv_id":null,"date":"2024-10-21","proceeding":"International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability (ARTIIS) 2024 10","authors":["Olivier Parisot"],"abstract":"Observing the sun with Electronically Assisted Astronomy allows understanding of solar phenomena, contributes to scientific research, promotes science education, and provides recreational enjoyment, all while requiring strict adherence to safety measures. In this paper, we present an annotated dataset of solar images captured with smart telescopes, and we show how this dataset allows to train Deep Learning YOLOv7 models for the detection of sunspots. Both data and Deep Learning model can be used by the general public to observe sun with contextual information.","url_abs":"https://www.doopyon.org/docs/publications/artiis2024-parisot.pdf","url_pdf":"https://www.doopyon.org/docs/publications/artiis2024-parisot.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"data-and-models-for-sunspots-detection-in","repo_url":"https://github.com/oparisot/SunspotsYoloDataset","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"astronomy","task_name":"Astronomy"},{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}