Levano Huamaccto, Marco; Montandon, E.

Support system in the detection of lesions of blackleg of oilseed rape, by means of image processing and artificial neural networks: Empirical case study preventive type for fungal alerts

datacite.alternateIdentifier.citation	9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018; N°8633678, 2019	en_US
datacite.alternateIdentifier.doi	10.1109/IISA.2018.8633678	en_US
datacite.creator	Levano Huamaccto, Marco
datacite.creator	Montandon, E.
datacite.date	2019
datacite.subject	Algoritmos
datacite.subject	Colza
datacite.subject	Hongos
datacite.subject	Procesamiento automático
datacite.subject	Enfermedad de la pata negra
datacite.title	Support system in the detection of lesions of blackleg of oilseed rape, by means of image processing and artificial neural networks: Empirical case study preventive type for fungal alerts	en_US
dc.date.accessioned	2020-07-27T18:50:22Z
dc.date.available	2020-07-27T18:50:22Z
dc.description.abstract	This paper proposes a framework for detecting lesions of blackleg of oilseed Rape. The idea of the investigation is to develop an algorithm of automatic processing that allows to recognize symptoms of an illness in Rape leaves, so a precise diagnostic can be made and make an early alert of the presence of the illness in Raps cultures, a typical agricultural activity in Araucanía Region. The application of these technique is beneficial for the development of informatic engineering for support of agronomy and agricultures. The study in focused in investigate and experiment the identification of failures in Rape by using digital image processing and artificial neuronal nets techniques	en_US
dc.format	PDF	en_US
dc.identifier.uri	http://repositoriodigital.uct.cl/handle/10925/2274
dc.language.iso	en	en_US
dc.source	IISA	en_US
oaire.resourceType	Artículo de Revista	en_US
uct.catalogador	pop	en_US
uct.comunidad	Ingeniería	en_US
uct.indizacion	SCOPUS	en_US