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	Provedor de dados Ciência Rural (1) REA (1) Autor Bazzi,Claudio L. (1) Lei,Xiangxiao (1) Nóbrega,Lúcia H. P. (1) Ouyang,Honglin (1) Rocha,Davi M. (1) Souza,Eduardo G. (1) Uribe-Opazo,Miguel A. (1) Xu,Lijuan (1) Mais... Palavra-chave Fuzzy clustering (2) Autocorrelation (1) Cross-correlation (1) Image segmentation. (1) Kernel (1) Machine vision (1) Management zones (1) Precision agriculture (1) Punica granatum L. (1) Spatial variability (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2019 (1) 2013 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Management zones definition using soil chemical and physical attributes in a soybean area REA Bazzi,Claudio L.; Souza,Eduardo G.; Uribe-Opazo,Miguel A.; Nóbrega,Lúcia H. P.; Rocha,Davi M.. Several equipments and methodologies have been developed to make available precision agriculture, especially considering the high cost of its implantation and sampling. An interesting possibility is to define management zones aim at dividing producing areas in smaller management zones that could be treated differently, serving as a source of recommendation and analysis. Thus, this trial used physical and chemical properties of soil and yield aiming at the generation of management zones in order to identify whether they can be used as recommendation and analysis. Management zones were generated by the Fuzzy C-Means algorithm and their evaluation was performed by calculating the reduction of variance and performing means tests. The division of the area into... Tipo: Info:eu-repo/semantics/article Palavras-chave: Precision agriculture; Spatial variability; Fuzzy clustering; Management zones; Autocorrelation; Cross-correlation. Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000500007 Mature pomegranate recognition methods in natural environments using machine vision Ciência Rural Lei,Xiangxiao; Ouyang,Honglin; Xu,Lijuan. ABSTRACT: The use of machine vision to recognize mature pomegranates in natural environments is of major significance in improving the applicability and work efficiency of picking robots. By analyzing the color characteristics of color images of mature pomegranates under different illumination conditions, the feasibility of the YCbCr color model for pomegranate image recognition under different illumination conditions was proven. First, the Cr component map of pomegranate image is selected and then the pomegranate fruit is segmented by the kernel fuzzy C-means clustering algorithm to obtain the pomegranate image. Contrast experiments of pomegranate image segmentation under different illumination conditions were then performed using the proposed kernel... Tipo: Info:eu-repo/semantics/article Palavras-chave: Punica granatum L.; Machine vision; Fuzzy clustering; Kernel; Image segmentation.. Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000900351 Registros recuperados: 2 Primeira ... 1 ... Última

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