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

Simple item page
dc.contributor.authorLevano Huamaccto, Marco
dc.contributor.authorMontandon, E.
dc.date2019
dc.date.accessioned2020-07-27T18:50:22Z
dc.date.available2020-07-27T18:50:22Z
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 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 techniquesen_US
dc.formatPDFen_US
dc.identifier.citation9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018; N°8633678, 2019en_US
dc.identifier.doi10.1109/IISA.2018.8633678en_US
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/2274
dc.language.isoenen_US
dc.sourceIISAen_US
dc.subjectAlgoritmos
dc.subjectColza
dc.subjectHongos
dc.subjectProcesamiento automático
dc.subjectEnfermedad de la pata negra
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 alertsen_US
dc.typeArtículo de Revistaen_US
uct.catalogadorpopen_US
uct.comunidadIngenieríaen_US
uct.indizacionSCOPUSen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Levano_Montandon_Support _2019.pdf
Size:
435.17 KB
Format:
Adobe Portable Document Format
Description:
Lectura de los datos del documento
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
803 B
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Ciencias de la Ingeniería