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Automated Weed Detection Systems: A Review

2020-06-02Journal article Open access
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dc.contributor.authorShanmugam, Saraswathi
dc.contributor.authorAssunção, Eduardo Timóteo
dc.contributor.authorMesquita, Ricardo
dc.contributor.authorVeiros, André
dc.contributor.authorGaspar, Pedro Dinis
dc.date.accessioned2020-07-10T09:44:36Z
dc.date.available2020-07-10T09:44:36Z
dc.date.issued2020-06-02
dc.description.abstractA weed plant can be described as a plant that is unwanted at a specific location at a given time. Farmers have fought against the weed populations for as long as land has been used for food production. In conventional agriculture this weed control contributes a considerable amount to the overall cost of the produce. Automatic weed detection is one of the viable solutions for efficient reduction or exclusion of chemicals in crop production. Research studies have been focusing and combining modern approaches and proposed techniques which automatically analyze and evaluate segmented weed images. This study discusses and compares the weed control methods and gives special attention in describing the current research in automating the weed detection and control.pt_PT
dc.description.sponsorshipThis study is within the activities of project PrunusBot - Sistema robótico aéreo autónomo de pulverização controlada e previsão de produção frutícola (autonomous unmanned aerial robotic system for controlled spraying and prediction of fruit production), Operation n.° PDR2020-101-031358 (líder), Consortium n.° 340, Initiative n.° 140 promoted by PDR2020 and co-financed by FEADER under the Portugal 2020 initiative.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSaraswathi Shanmugam, Eduardo Assunção, Ricardo Mesquita, André Veiros, and Pedro D. Gaspar, (2020), “Automated Weed Detection Systems: A Review” in International Congress on Engineering — Engineering for Evolution, KnE Engineering, pages 271–284. DOI 10.18502/keg.v5i6.7046pt_PT
dc.identifier.doidoi.org/10.18502/keg.v5i6.7046pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/10343
dc.language.isoengpt_PT
dc.publisherPublishing services provided by Knowledge Ept_PT
dc.subjectDetectionpt_PT
dc.subjectWeedpt_PT
dc.subjectAgriculture 4.0pt_PT
dc.subjectComputational visionpt_PT
dc.subjectRoboticspt_PT
dc.titleAutomated Weed Detection Systems: A Reviewpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage284pt_PT
oaire.citation.startPage271pt_PT
oaire.citation.titleKnowledge Ept_PT
person.familyNameshanmugam
person.familyNameAssunção
person.familyNameMesquita
person.familyNameVeiros
person.familyNameGaspar
person.givenNamesaraswathi
person.givenNameEduardo Timóteo
person.givenNameRicardo
person.givenNameAndré
person.givenNamePedro Dinis
person.identifier.ciencia-id421E-B6CA-E3A1
person.identifier.ciencia-id6111-9F05-2916
person.identifier.orcid0000-0003-2569-3256
person.identifier.orcid0000-0001-6027-7763
person.identifier.orcid0000-0002-8599-6737
person.identifier.orcid0000-0001-6901-795X
person.identifier.orcid0000-0003-1691-1709
person.identifier.ridN-3016-2013
person.identifier.scopus-author-id57419570900
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscovery28246162-71e5-4d51-82c5-229db0aad6aa

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