Recognition of Plant Diseases Using Convolutional Neural Networks

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dc.contributor.advisorCervantes-Álvarez, José F.
dc.contributor.authorLeón-Lemus, Cyntia D.
dc.date.accessioned2020-09-29T23:44:28Z
dc.date.available2020-09-29T23:44:28Z
dc.date.issued2020-02
dc.descriptionEarly detection of diseases in crops for human consumption is crucial for agricultural production in the world. Nowadays, Deep learning algorithms are used for the analysis and classification of images such as the convolutional neural network used to detect diseases in plants. Unfortunately, these algorithms still need a lot of computation to obtain results that could take hours, days, or maybe weeks for a prediction. This paper aims to provide an analysis of how the Wavelet transform in distributed platforms can provide competitive results with a fraction of the resources used comparatively in time and memory used to detect diseases in tomato leaves.es_MX
dc.identifier.citationLeón-Lemus, C. D. (2020). Recognition of Plant Diseases Using Convolutional Neural Networks. Trabajo de obtención de grado, Maestría en Sistemas Computacionales. Tlaquepaque, Jalisco: ITESO.es_MX
dc.identifier.urihttps://hdl.handle.net/11117/6336
dc.language.isospaes_MX
dc.publisherITESOes_MX
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes_MX
dc.subjectConvolutional Neural Networkses_MX
dc.subjectDetection of Diseaseses_MX
dc.titleRecognition of Plant Diseases Using Convolutional Neural Networkses_MX
dc.typeinfo:eu-repo/semantics/masterThesises_MX
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_MX

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