Automatic image-based detection and recognition of plant diseases - a critical view.

BARBEDO, J. G. A.

Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083285

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DC Field	Value	Language
dc.contributor.author	BARBEDO, J. G. A.
dc.date.accessioned	2017-12-23T23:19:13Z	-
dc.date.available	2017-12-23T23:19:13Z	-
dc.date.created	2017-12-21
dc.date.issued	2017
dc.identifier.citation	In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 11., 2017, Campinas. Ciência de dados na era da agricultura digital: anais. Campinas: Editora da Unicamp: Embrapa Informática Agropecuária, 2017.
dc.identifier.isbn	978-85-85783-75-4
dc.identifier.uri	http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083285	-
dc.description	This paper presents a critical analysis of the current state and future perspectives for the use of digital images applied to plant pathology. The differences between the processes of automatic detection and recognition of diseases in plants are presented, with emphasis on the respective current challenges and difficulties. Some of the limitations intrinsic to the use of digital images for detection and recognition of diseases are discussed. Because some of those limitations are mostly inevitable, they may require the use of ancillary data, which may not always be obtained automatically. As a result, depending on the application, the development of completely automatic diagnosis methods may be unfeasible. Thus, the main objective of this paper is to show that one of the main causes for the low relevance attributed to most algorithms proposed so far is the lack of knowledge by the researchers, especially regarding the real difficulties involved in the diagnosis process. The text concludes showing that significant advancements in this area will only be achieved through careful experimental delineation, realistic objectives, and construction of an image database capable of suitably represent all variations expected to occur within the scope of the algorithm to be developed.
dc.language.iso	eng	eng
dc.rights	openAccess	eng
dc.subject	Processamento de imagem
dc.subject	Diagnóstico de doenças
dc.subject	Fitopatologia	pt_BR
dc.title	Automatic image-based detection and recognition of plant diseases - a critical view.
dc.type	Artigo em anais e proceedings
dc.date.updated	2020-01-21T11:11:11Z	pt_BR
dc.subject.nalthesaurus	Image analysis
dc.subject.nalthesaurus	Disease diagnosis
dc.subject.nalthesaurus	Plant pathology
dc.description.notes	SBIAgro 2017.
dc.format.extent2	p. 69-77.
riaa.ainfo.id	1083285
riaa.ainfo.lastupdate	2020-01-21 -02:00:00
dc.contributor.institution	JAYME GARCIA ARNAL BARBEDO, CNPTIA.
Appears in Collections:	Artigo em anais de congresso (CNPTIA)

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