Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/33511
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dc.contributor.authorNabitchita, Batictéen_US
dc.contributor.authorGonçalves, Norberto Jorgeen_US
dc.contributor.authorCoelho, Paulo Jorgeen_US
dc.contributor.authorPimenta, Luísen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.contributor.authorLameski, Petreen_US
dc.contributor.authorCosta, Mónicaen_US
dc.contributor.authorNeves, Paulo Alexandreen_US
dc.contributor.authorPires, Ivan Miguelen_US
dc.date.accessioned2025-05-13T06:30:14Z-
dc.date.available2025-05-13T06:30:14Z-
dc.date.issued2024-01-17-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/33511-
dc.description.abstract<jats:p>Nowadays, the object’s volume is essential for monitoring any scene. Technological equipment is evolving, and mobile devices and other devices embed high-resolution cameras. The high-resolution cameras open a window for different research studies, where the volume measurement is vital for different areas. This study aims to identify image processing techniques for measuring the object’s volume. Thus, a systematic review was performed with a Natural Language Processing (NLP)-based framework for identifying studies between 2010 and 2023 related to the measurement of object volume. As a result of this search, this paper reviewed and analyzed 25 studies, verifying that different computer vision methods accurately handle object recognition. Additionally, an evaluation of the databases presented by the studies above is performed to consider further the design of a new approach to infer the volume of objects from an image.</jats:p>en_US
dc.publisherSAGE Publicationsen_US
dc.relation.ispartofJournal of Ambient Intelligence and Smart Environmentsen_US
dc.titleMethods for volume inference of non-medical objects from images: A short reviewen_US
dc.identifier.doi10.3233/ais-230193-
dc.identifier.urlhttps://content.iospress.com/download?id=10.3233/AIS-230193-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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