Publication
Artificial intelligence to identify olive-tree cultivars
| dc.contributor.author | Mendes, João | |
| dc.contributor.author | Lima, José | |
| dc.contributor.author | Costa, Lino | |
| dc.contributor.author | Pereira, Ana I. | |
| dc.date.accessioned | 2023-03-01T12:28:51Z | |
| dc.date.available | 2023-03-01T12:28:51Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The exponential advance in artificial intelligence techniques makes it possible to apply them to previously thought to be impossible sectors. In this work, a different approach is presented to identify the different varieties of olive trees present in the olive groves of Portugal. Using its leaves and deep learning algorithms necessary for its classification, the proposed system can perform a reliable, low-cost, and real-time identification of the olive trees. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Mendes, João; Lima, José; Costa, Lino; Pereira, Ana I. (2022). Artificial intelligence to identify olive-tree cultivars. In 2nd Symposium of Applied Science for Young Researchers. Viana do Castelo | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10198/27370 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Artificial intelligence | pt_PT |
| dc.subject | Olive | pt_PT |
| dc.subject | Classification | pt_PT |
| dc.title | Artificial intelligence to identify olive-tree cultivars | pt_PT |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Viana do Castelo | pt_PT |
| oaire.citation.title | 2nd Symposium of Applied Science for Young Researchers | pt_PT |
| person.familyName | Mendes | |
| person.familyName | Lima | |
| person.familyName | Pereira | |
| person.givenName | João | |
| person.givenName | José | |
| person.givenName | Ana I. | |
| person.identifier | 2726655 | |
| person.identifier | R-000-8GD | |
| person.identifier.ciencia-id | EA1F-844D-6BA9 | |
| person.identifier.ciencia-id | 6016-C902-86A9 | |
| person.identifier.ciencia-id | 0716-B7C2-93E4 | |
| person.identifier.orcid | 0000-0003-0979-8314 | |
| person.identifier.orcid | 0000-0001-7902-1207 | |
| person.identifier.orcid | 0000-0003-3803-2043 | |
| person.identifier.rid | L-3370-2014 | |
| person.identifier.rid | F-3168-2010 | |
| person.identifier.scopus-author-id | 57225794972 | |
| person.identifier.scopus-author-id | 55851941311 | |
| person.identifier.scopus-author-id | 15071961600 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | b5c9de22-cf9e-47b8-b7a4-26e08fb12b28 | |
| relation.isAuthorOfPublication | d88c2b2a-efc2-48ef-b1fd-1145475e0055 | |
| relation.isAuthorOfPublication | e9981d62-2a2b-4fef-b75e-c2a14b0e7846 | |
| relation.isAuthorOfPublication.latestForDiscovery | d88c2b2a-efc2-48ef-b1fd-1145475e0055 |