{"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/deepscores-and-deep-watershed-detection","title":"DeepScores and Deep Watershed Detection: current state and open issues","arxiv_id":"1810.05423","date":"2018-10-12","proceeding":null,"authors":["Ismail Elezi","Lukas Tuggener","Marcello Pelillo","Thilo Stadelmann"],"abstract":"This paper gives an overview of our current Optical Music Recognition (OMR)\nresearch. We recently released the OMR dataset \\emph{DeepScores} as well as the\nobject detection method \\emph{Deep Watershed Detector}. We are currently taking\nsome additional steps to improve both of them. Here we summarize current and\nfuture efforts, aimed at improving usefulness on real-world task and tackling\nextreme class imbalance.","url_abs":"http://arxiv.org/abs/1810.05423v1","url_pdf":"http://arxiv.org/pdf/1810.05423v1.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":"deepscores-and-deep-watershed-detection","repo_url":"https://github.com/tuggeluk/DeepWatershedDetection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}