Publication
Computer vision algorithms for 3D object recognition and orientation: a bibliometric study
| dc.contributor.author | Yahia, Youssef | |
| dc.contributor.author | Lopes, Júlio Castro | |
| dc.contributor.author | Lopes, Rui Pedro | |
| dc.date.accessioned | 2023-12-20T16:36:20Z | |
| dc.date.available | 2023-12-20T16:36:20Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This paper consists of a bibliometric study that covers the topic of 3D object detection from 2022 until the present day. It employs various analysis approaches that shed light on the leading authors, affiliations, and countries within this research domain alongside the main themes of interest related to it. The findings revealed that China is the leading country in this domain given the fact that it is responsible for most of the scientific literature as well as being a host for the most productive universities and authors in terms of the number of publications. China is also responsible for initiating a significant number of collaborations with various nations around the world. The most basic theme related to this field is deep learning, along with autonomous driving, point cloud, robotics, and LiDAR. The work also includes an in-depth review that underlines some of the latest frameworks that took on various challenges regarding this topic, the improvement of object detection from point clouds, and training end-to-end fusion methods using both camera and LiDAR sensors, to name a few. | pt_PT |
| dc.description.sponsorship | This research was funded by the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Yahia, Youssef; Lopes, Júlio Castro; Lopes, Rui Pedro (2023). Computer vision algorithms for 3D object recognition and orientation: a bibliometric study. Electronics. eISSN 2079-9292. 12:20, p. 1-16 | pt_PT |
| dc.identifier.doi | 10.3390/electronics12204218 | pt_PT |
| dc.identifier.eissn | 2079-9292 | |
| dc.identifier.uri | http://hdl.handle.net/10198/29000 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI | pt_PT |
| dc.relation | LA/P/0007/2021 | pt_PT |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | 3D object | pt_PT |
| dc.subject | Object detection | pt_PT |
| dc.subject | Object orientation | pt_PT |
| dc.subject | Bibliometric analysis | pt_PT |
| dc.title | Computer vision algorithms for 3D object recognition and orientation: a bibliometric study | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT | |
| oaire.citation.endPage | 16 | pt_PT |
| oaire.citation.issue | 20 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | Electronics | pt_PT |
| oaire.citation.volume | 12 | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Lopes | |
| person.givenName | Rui Pedro | |
| person.identifier.ciencia-id | 8E14-54E4-4DB5 | |
| person.identifier.orcid | 0000-0002-9170-5078 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | e1e64423-0ec8-46ee-be96-33205c7c98a9 | |
| relation.isAuthorOfPublication.latestForDiscovery | e1e64423-0ec8-46ee-be96-33205c7c98a9 | |
| relation.isProjectOfPublication | 6e01ddc8-6a82-4131-bca6-84789fa234bd | |
| relation.isProjectOfPublication | d0a17270-80a8-4985-9644-a04c2a9f2dff | |
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