Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125314
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dc.contributor.authorBARBEDO, J. G. A.
dc.date.accessioned2020-10-07T09:14:47Z-
dc.date.available2020-10-07T09:14:47Z-
dc.date.created2020-10-06
dc.date.issued2020
dc.identifier.citationAI, v. 1, n. 2, p. 312-328, June 2020.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1125314-
dc.descriptionAbstract: Pest management is among the most important activities in a farm. Monitoring all different species visually may not be effective, especially in large properties. Accordingly, considerable research effort has been spent towards the development of effective ways to remotely monitor potential infestations. A growing number of solutions combine proximal digital images with machine learning techniques, but since species and conditions associated to each study vary considerably, it is difficult to draw a realistic picture of the actual state of the art on the subject. In this context, the objectives of this article are (1) to briefly describe some of the most relevant investigations on the subject of automatic pest detection using proximal digital images and machine learning; (2) to provide a unified overview of the research carried out so far, with special emphasis to research gaps that still linger; (3) to propose some possible targets for future research.
dc.language.isoeng
dc.rightsopenAccesseng
dc.subjectAprendizado de máquina
dc.subjectImagem digital
dc.subjectImagens digitais
dc.subjectMonitoramento de pragas
dc.subjectPest detection
dc.subjectMachine learning
dc.subjectAgricultural crops
dc.titleDetecting and classifying pests in crops using proximal images and machine learning: a review.
dc.typeArtigo de periódico
dc.subject.thesagroInfestação
dc.subject.thesagroInseto
dc.subject.nalthesaurusPest monitoring
dc.subject.nalthesaurusInsects
dc.subject.nalthesaurusDigital images
riaa.ainfo.id1125314
riaa.ainfo.lastupdate2020-10-08 -03:00:00
dc.identifier.doihttps://doi.org/10.3390/ai1020021
dc.contributor.institutionJAYME GARCIA ARNAL BARBEDO, CNPTIA.
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