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Morphological perceptrons with competitive learning: Lattice-theoretical framework and constructive learning algorithm
(Elsevier Science IncNew YorkEUA, 2011)
Hybrid neural networks with morphological neurons and perceptrons
(2020-03-04)
RESUMEN:
En el área de Aprendizaje de Máquina (Machine Learning (ML)) existen diversas arquitecturas de redes neuronales. Arquitecturas que por décadas han utilizado las mismas unidades de cómputo para la clasificación ...
Proposta de uma Classe de Perceptrons Híbridos com Aprendizagem baseada em Gradiente Descendente
(Universidade Federal de Pernambuco, 2014)
Inteligência computacional aplicada ao estudo da divergência e fenotipagem em cultivares de soja
(Universidade Federal de Minas GeraisUFMG, 2018-02-15)
The artificial neural networks are computational models of the human brain that recognize patterns and regularities of the data and represent an alternative as a universal approximation of complex functions. They may ...
Intelligent classification models for food products basis on morphological, colour and texture features
(Universidad Nacional de Colombia - Sede Palmira, 2017-10-01)
The aim of this paper is to build a supervised intelligent classification model of food products such as Biscuits, Cereals, Vegetables, Edible nuts and etc., using digital images. The Correlation-based Feature Selection ...
Estimativa de nitrogênio em Annona emarginata (Schltdl.) H. Rainer utilizando espectroscopia no infravermelho próximo (NIRS): Uma abordagem estatística e computacional
(Universidade Estadual Paulista (Unesp), 2020-02-18)
O nitrogênio é um elemento mineral essencial para as plantas. Sua deficiência em fases iniciais do desenvolvimento pode gerar alterações fisiológicas e morfológicas que reduzem o crescimento e conflui na não expressão total ...
Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks
(2011-10-24)
The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for ...
Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks
(2011-10-24)
The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for ...