A Comparative Study on Morphological Neural Networks for Binary Classification

  • Luana Felipe de Barros UNICAMP
  • Marcos Eduardo Valle UNICAMP

Resumo


Redes neurais morfológicas representam uma classe de redes neurais artificiais cujos neurônios efetuam uma operação da morfologia matemática seguida da aplicação de uma função de ativação. Este artigo apresenta um estudo comparativo de diferentes abordagens que utilizam redes neurais morfológicas. Especificamente, de acordo com a regra de treinamento, revisamos abordagens incrementais, baseadas no método de máxima descida, máquinas de aprendizado extremo e procedimento de otimização convexa-côncava. Experimentos computacionais mostraram que, em média, o perceptron erosão-dilatação reduzido com as estratégias bagging e ensemble obteve melhores resultados em diversos problemas de classificação binária.

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Publicado
29/11/2021
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BARROS, Luana Felipe de; VALLE, Marcos Eduardo. A Comparative Study on Morphological Neural Networks for Binary Classification. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 655-666. DOI: https://doi.org/10.5753/eniac.2021.18292.