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Data classification is present in different real problems, such asrecognizing patterns in images, differentiating defective parts in a productionline, classifying benign and malignant tumors, among many others. Many of theseproblems have data patterns that are hard to identify, which requires moreadvanced techniques for resolution. Recently, several works addressingdifferent artificial neural network architectures have been applied to solveclassification problems. When the classification problem must be obtainedthrough images, currently, the standard methodology is the use of convolutionalneural networks. Thus, in this report convolutional neural networks are used toclassify fish species.  Classifica\c{c}\~ao de dados est\'a presente em diversos problemas reais,tais como: reconhecer padr\~oes em imagens, diferenciar pe\c{c}as defeituosasem uma linha de produ\c{c}\~ao, classificar tumores benignos e malignos, dentrediversas outras. Muitos desses problemas possuem padr\~oes de dados dif\'iceisde serem identificados, o que requer, consequentemente, t\'ecnicas maisavan\c{c}adas para sua resolu\c{c}\~ao. Recentemente, diversos trabalhosabordando diferentes arquiteturas de redes neurais artificiais v\^em sendoaplicados para solucionar problemas de classifica\c{c}\~ao. Quando aclassifica\c{c}\~ao do problema deve ser obtida por meio de imagens, atualmentea metodologia padr\~ao \'e uso de redes neurais convolucionais. Sendo assim,neste trabalho s\~ao utilizadas redes neurais convolucionais paraclassifica\c{c}\~ao de esp\'ecies de peixes.

Classifica\c{c}\~ao de esp\'ecies de peixe utilizando redes neurais convolucional