Publication
Detecting and monitoring the development stages of wild flowers and plants using computer vision: approaches, challenges and opportunities
| dc.contributor.author | Videira, João | |
| dc.contributor.author | Gaspar, Pedro Dinis | |
| dc.contributor.author | Soares, V.N.G.J. | |
| dc.contributor.author | Caldeira, J.M.L.P. | |
| dc.date.accessioned | 2023-10-16T16:38:52Z | |
| dc.date.available | 2023-10-16T16:38:52Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Wild flowers and plants play an important role in protecting biodiversity and providing various ecosystem services. However, some of them are endangered or threatened and are entitled to preservation and protection. This study represents a first step to develop a computer vision system and a supporting mobile app for detecting and monitoring the development stages of wild flowers and plants, aiming to contribute to their preservation. It first introduces the related concepts. Then, surveys related work and categorizes existing solutions presenting their key features, strengths, and limitations. The most promising solutions and techniques are identified. Insights on open issues and research directions in the topic are also provided. This paper paves the way to a wider adoption of recent results in computer vision techniques in this field and for the proposal of a mobile application that uses YOLO convolutional neural networks to detect the stages of development of wild flowers and plants. | pt_PT |
| dc.description.sponsorship | J.M.L.P.C. and V.N.G.J.S. acknowledge that this work is funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/50008/2020. P.D.G. thanks the support provided by the Center for Mechanical and Aerospace Science and Technologies (C-MAST) under project UIDB/00151/2020. This is within the activities of project Montanha Viva – An intelligent prediction system for decision support in sustainability, project PD21-00009, promoted by PROMOVE program funded by Fundação La Caixa and supported by Fundação para a Ciência e a Tecnologia and BPI. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | VIDEIRA, João [et al.] (2023) - Detecting and monitoring the development stages of wild flowers and plants using computer vision: approaches, challenges and opportunities. International Journal of Advances in Intelligent Informatics. Vol. 9, n.º 3, p. DOI: 10.26555/ijain.v9i3.1012 | pt_PT |
| dc.identifier.doi | 10.26555/ijain.v9i3.1012 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.11/8678 | |
| 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 | Wild flowers | pt_PT |
| dc.subject | Development stages | pt_PT |
| dc.subject | Computer vision | pt_PT |
| dc.subject | Machine learning | pt_PT |
| dc.subject | Deep learning | pt_PT |
| dc.title | Detecting and monitoring the development stages of wild flowers and plants using computer vision: approaches, challenges and opportunities | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.issue | 3 | pt_PT |
| oaire.citation.startPage | 347 | pt_PT |
| oaire.citation.title | International Journal of Advances in Intelligent Informatics | pt_PT |
| oaire.citation.volume | 9 | pt_PT |
| person.familyName | Gaspar | |
| person.familyName | Caldeira | |
| person.givenName | Pedro Dinis | |
| person.givenName | João | |
| person.identifier | a4GD8aoAAAAJ | |
| person.identifier.ciencia-id | 6111-9F05-2916 | |
| person.identifier.ciencia-id | 5B19-E130-E382 | |
| person.identifier.ciencia-id | A91B-85B8-C27E | |
| person.identifier.orcid | 0000-0003-1691-1709 | |
| person.identifier.orcid | 0000-0002-8057-5474 | |
| person.identifier.orcid | 0000-0001-5830-3790 | |
| person.identifier.rid | N-3016-2013 | |
| person.identifier.scopus-author-id | 57419570900 | |
| person.identifier.scopus-author-id | 27067580500 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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