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dc.date.accessioned 2012-11-07T13:40:00Z
dc.date.available 2012-11-07T13:40:00Z
dc.date.issued 2012-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23812
dc.description.abstract The Yerba Mate quality is defined by estimating the product moisture content. This value allows adjusting the production system, by controlling the stake of the dryer to ensure the product quality. Currently this process is done manually. However, this paper presents a first approach method to estimate the moisture contents of Yerba Mate leaves through image processing techniques. The output of the proposed system is established by a neural network MLPBP, which quantifies the level of moisture for a given sample. Also present the results of applying the proposed method to a set of 55 samples collected in a Yerba Mate production establishment. en
dc.language en es
dc.subject Neural nets es
dc.subject Yerba Mate moisture quantization en
dc.subject image processing en
dc.subject Signal processing es
dc.subject artificial neural networks en
dc.subject Real time es
dc.title Quantization of moisture content in yerba mate leaves through image processing en
dc.type Objeto de conferencia es
sedici.creator.person Leiva, Lucas es
sedici.creator.person Acosta, Nelson es
sedici.description.note Eje: Workshop Procesamiento de señales y sistemas de tiempo real (WPSTR) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2012-10
sedici.relation.event XVIII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)