{"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/scene-learning-recognition-and-similarity","title":"Scene learning, recognition and similarity detection in a fuzzy ontology via human examples","arxiv_id":"1709.09433","date":"2017-09-27","proceeding":null,"authors":["Luca Buoncompagni","Fulvio Mastrogiovanni","Alessandro Saffiotti"],"abstract":"This paper introduces a Fuzzy Logic framework for scene learning, recognition\nand similarity detection, where scenes are taught via human examples. The\nframework allows a robot to: (i) deal with the intrinsic vagueness associated\nwith determining spatial relations among objects; (ii) infer similarities and\ndissimilarities in a set of scenes, and represent them in a hierarchical\nstructure represented in a Fuzzy ontology. In this paper, we briefly formalize\nour approach and we provide a few use cases by way of illustration.\nNevertheless, we discuss how the framework can be used in real-world scenarios.","url_abs":"http://arxiv.org/abs/1709.09433v1","url_pdf":"http://arxiv.org/pdf/1709.09433v1.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":"scene-learning-recognition-and-similarity","repo_url":"https://github.com/EmaroLab/fuzzy_sit","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}