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Master's Dissertation
DOI
10.11606/D.18.2007.tde-30102007-141411
Document
Author
Full name
Cíntia Beatriz de Souza Silva
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2007
Supervisor
Committee
Silva, Ivan Nunes da (President)
Cliquet Júnior, Alberto
Colnago, Luiz Alberto
Title in Portuguese
Processamento de sinais de ressonância magnética nuclear usando classificador neural para reconhecimento de carne bovina
Keywords in Portuguese
Classificação de padrões
Redes neurais artificiais
Ressonância magnética nuclear
Abstract in Portuguese
Garantir a qualidade da carne bovina produzida no Brasil tem sido uma preocupação dos produtores, pois contribui para aumentar a exportação e o consumo interno do produto. Por isso, tem-se pesquisado novos métodos que analisam e garantam a qualidade da carne, de forma rápida, eficiente e não destrutiva. A ressonância magnética nuclear (RMN) tem se destacado como uma das técnicas de controle de qualidade de carne. Neste trabalho as redes neurais artificiais estão sendo utilizadas para o reconhecimento de padrões dos dados de ressonância magnética nuclear oriundos de carne bovina. Mais especificamente, os respectivos dados têm sido utilizados por uma rede perceptron multicamadas para a extração de características da carne bovina, possibilitando a classificação do grupo genético e do sexo dos animais a partir de uma amostra da referida carne. Os resultados dos experimentos são também apresentados para ilustrar o desempenho da abordagem proposta.
Title in English
Signal processing of nuclear magnetic resonance using neural classification for bovine meat recognition
Keywords in English
Artificial neural network
Nuclear magnetic resonance
Pattern classification
Abstract in English
Guaranteeing the quality of the bovine meat produced in Brazil has been a concern of the producers because it contributes to increase the export and the domestic consumption of the product. Therefore, new methods have been researched that analyze and guarantee the quality of the meat in a fast, efficient and non destructive way. Nuclear magnetic resonance (NMR) has been highlighted as one of the techniques of meat quality control. In this work study artificial neural networks are being used for pattern recognition from data obtained by the resonance equipment, originating from bovine meat. More specifically, the respective data have been used by a multilayer perceptron network for extraction of bovine meat characteristics, making possible the classification of both genetic group and animal sex starting from a single meat sample. Several results of experimental tests are also presented to illustrate the performance of the proposed approach.
 
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dissertacao.PDF (2.72 Mbytes)
Publishing Date
2007-11-12
 
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