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

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dc.contributor.authorLévano Huamaccto, Marcos
dc.contributor.authorMontandon, Esteban
dc.contributor.authorIEEE
dc.date2018
dc.date.accessioned2021-04-30T17:07:20Z
dc.date.available2021-04-30T17:07:20Z
dc.description.abstractThis 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 Araucania 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.
dc.identifier.citation2018 9TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA),Vol.,400-405,2018
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/4087
dc.language.isoen
dc.publisherIEEE
dc.source2018 9TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA)
dc.subject.englishsystem
dc.subject.englishpattern recognition
dc.subject.englishalgorithm
dc.subject.englishfungi
dc.subject.englishautomatic processing
dc.titleSupport 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
dc.typeMeeting
uct.catalogadorWOS
uct.indizacionISTP
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