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Automatic corn (Zea mays) kernel inspection system using novelty detection based on principal component analysis

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Automatic corn (Zea mays) kernel inspection system using novelty detection based on principal component analysis

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Valiente González, JM.; Andreu García, G.; Potter, P.; Rodas Jordá, Á. (2014). Automatic corn (Zea mays) kernel inspection system using novelty detection based on principal component analysis. Biosystems Engineering. 117(1):94-103. doi:10.1016/j.biosystemseng.2013.09.003

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Title: Automatic corn (Zea mays) kernel inspection system using novelty detection based on principal component analysis
Author: Valiente González, José Miguel Andreu García, Gabriela Potter, Paulus Rodas Jordá, Ángel
UPV Unit: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
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Abstract:
[EN] Corn (Zea mays) kernel processing companies evaluate the quality of kernels to determine the price of a batch. Human inspectors in labs inspect a reduced set of kernels to estimate the proportion of damaged kernels ...[+]
Subjects: Image acquisition system , Computer vision , PCA , Novelty detection
Copyrigths: Cerrado
Source:
Biosystems Engineering. (issn: 1537-5110 )
DOI: 10.1016/j.biosystemseng.2013.09.003
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.biosystemseng.2013.09.003
Conference name: 4th International Workshop on Computer Image Analysis in Agriculture, held at CIGR-AgEng
Conference place: Valencia, Spain
Conference date: July 08-12, 2012
Thanks:
We acknowledge the support of the Spanish company DACSA Maiceras Españolas S.A. in supplying the dent corn samples
Type: Artículo Comunicación en congreso

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