{"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/noisy-supervision-for-correcting-misaligned","title":"Noisy Supervision for Correcting Misaligned Cadaster Maps Without Perfect Ground Truth Data","arxiv_id":"1903.06529","date":"2019-03-12","proceeding":null,"authors":["Nicolas Girard","Guillaume Charpiat","Yuliya Tarabalka"],"abstract":"In machine learning the best performance on a certain task is achieved by\nfully supervised methods when perfect ground truth labels are available.\nHowever, labels are often noisy, especially in remote sensing where manually\ncurated public datasets are rare. We study the multi-modal cadaster map\nalignment problem for which available annotations are mis-aligned polygons,\nresulting in noisy supervision. We subsequently set up a multiple-rounds\ntraining scheme which corrects the ground truth annotations at each round to\nbetter train the model at the next round. We show that it is possible to reduce\nthe noise of the dataset by iteratively training a better alignment model to\ncorrect the annotation alignment.","url_abs":"http://arxiv.org/abs/1903.06529v1","url_pdf":"http://arxiv.org/pdf/1903.06529v1.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":"noisy-supervision-for-correcting-misaligned","repo_url":"https://github.com/Lydorn/mapalignment","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1903.06529","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}