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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datacite.alternateIdentifier.citation2018 9TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA),Vol.,400-405,2018
datacite.creatorLévano Huamaccto, Marcos
datacite.creatorMontandon, Esteban
datacite.creatorIEEE
datacite.date2018
datacite.subject.englishsystem
datacite.subject.englishpattern recognition
datacite.subject.englishalgorithm
datacite.subject.englishfungi
datacite.subject.englishautomatic processing
datacite.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.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.urihttp://repositoriodigital.uct.cl/handle/10925/4087
dc.language.isoen
dc.publisherIEEE
dc.source2018 9TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA)
oaire.resourceTypeMeeting
uct.catalogadorWOS
uct.indizacionISTP
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