Detection of Citrus Canker and Huanglongbing Using Fluorescence Imaging Spectroscopy (FIS) Technique and Two Different Computational Methods: Support Vector Machine and Neural Network

Caio B. Wetterich; Ruan Felipe de Oliveira Neves; José Belasque Junior; Luis G. Marcassa

doi:10.1364/FIO.2015.FW5E.4

Frontiers in Optics 2015
OSA Technical Digest (online) (Optica Publishing Group, 2015),
paper FW5E.4
•https://doi.org/10.1364/FIO.2015.FW5E.4

Detection of Citrus Canker and Huanglongbing Using Fluorescence Imaging Spectroscopy (FIS) Technique and Two Different Computational Methods: Support Vector Machine and Neural Network

Caio B. Wetterich, Ruan Felipe de Oliveira Neves, José Belasque Junior, and Luis G. Marcassa

Frontiers in Optics 2015

San Jose, California United States
18–22 October 2015
ISBN: 978-1-943580-03-3

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General Optics in Biology and Medicine (FW5E)

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C. B. Wetterich, R. F. de Oliveira Neves, J. B. Junior, and L. G. Marcassa, "Detection of Citrus Canker and Huanglongbing Using Fluorescence Imaging Spectroscopy (FIS) Technique and Two Different Computational Methods: Support Vector Machine and Neural Network," in Frontiers in Optics 2015, OSA Technical Digest (online) (Optica Publishing Group, 2015), paper FW5E.4.

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Abstract

We have used FIS to investigate citrus diseases. Texture features were extracted and used as input into classifiers. Results show that is possible differentiate the diseases that have similar symptoms using these two computational methods.

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