{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:07:16Z","timestamp":1774627636288,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T00:00:00Z","timestamp":1680825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The reconstruction of 3D geometries starting from reality-based data is challenging and time-consuming due to the difficulties involved in modeling existing structures and the complex nature of built heritage. This paper presents a methodological approach for the automated segmentation and classification of surveying outputs to improve the interpretation and building information modeling from laser scanning and photogrammetric data. The research focused on the surveying of reticular, space grid structures of the late 19th\u201320th\u201321st centuries, as part of our architectural heritage, which might require monitoring maintenance activities, and relied on artificial intelligence (machine learning and deep learning) for: (i) the classification of 3D architectural components at multiple levels of detail and (ii) automated masking in standard photogrammetric processing. Focusing on the case study of the grid structure in steel named La Vela in Bologna, the work raises many critical issues in space grid structures in terms of data accuracy, geometric and spatial complexity, semantic classification, and component recognition.<\/jats:p>","DOI":"10.3390\/rs15081961","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T03:19:54Z","timestamp":1681096794000},"page":"1961","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Machine Learning and Deep Learning for the Built Heritage Analysis: Laser Scanning and UAV-Based Surveying Applications on a Complex Spatial Grid Structure"],"prefix":"10.3390","volume":"15","author":[{"given":"Dario","family":"Billi","sequence":"first","affiliation":[{"name":"Department of Civil and Industrial Engineering, ASTRO Laboratory, University of Pisa, L.go Lucio Lazzarino, 56122 Pisa, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9601-3145","authenticated-orcid":false,"given":"Valeria","family":"Croce","sequence":"additional","affiliation":[{"name":"Department of Energy, Systems, Land and Construction Engineering, University of Pisa, 56122 Pisa, Italy"}]},{"given":"Marco Giorgio","family":"Bevilacqua","sequence":"additional","affiliation":[{"name":"Department of Energy, Systems, Land and Construction Engineering, University of Pisa, 56122 Pisa, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3065-0616","authenticated-orcid":false,"given":"Gabriella","family":"Caroti","sequence":"additional","affiliation":[{"name":"Department of Civil and Industrial Engineering, ASTRO Laboratory, University of Pisa, L.go Lucio Lazzarino, 56122 Pisa, Italy"}]},{"given":"Agnese","family":"Pasqualetti","sequence":"additional","affiliation":[{"name":"IBS Progetti Chianciano Terme, 53042 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0582-5314","authenticated-orcid":false,"given":"Andrea","family":"Piemonte","sequence":"additional","affiliation":[{"name":"Department of Civil and Industrial Engineering, ASTRO Laboratory, University of Pisa, L.go Lucio Lazzarino, 56122 Pisa, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0869-6703","authenticated-orcid":false,"given":"Michele","family":"Russo","sequence":"additional","affiliation":[{"name":"Department of History, Representation and Restoration of Architecture, Sapienza University of Rome, Via del Castro Laurenziano 7\/a, 00161 Rome, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/978-3-319-68646-2_7","article-title":"Digital Technology and Mechatronic Systems for the Architectural 3D Metric Survey","volume":"Volume 92","author":"Ottaviano","year":"2018","journal-title":"Mechatronics for Cultural Heritage and Civil Engineering"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.patrec.2020.02.017","article-title":"Machine Learning for Cultural Heritage: A Survey","volume":"133","author":"Fiorucci","year":"2020","journal-title":"Pattern Recognit. 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